Mathematics & computational sciences prospectus - Walter Sisulu ... [PDF]

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SCHOOL OF MATHEMATICAL AND. COMPUTATIONAL SCIENCES. 2. TABLE OF ...... The maximum period for the degree programme is three years. See also ...
Walter Sisulu University PROSPECTUS 2014

Faculty of Science, Engineering and Technology School of Mathematical & Computational Sciences

www.wsu.ac.za

FACULTY OF SCIENCE, ENGINEERING AND TECHNOLOGY SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES PROSPECTUS 2014

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PROSPECTUS

TABLE OF CONTENTS 1 SCHOOL ADMINISTRATIVE STAFF .................................................................................. 5 1.1 Departments Academic and Administrative Staff............................................................... 5 1.1.1 Department of Applied Mathematics................................................................................ 5 1.1.1.1 Academic Staff.............................................................................................................. 5 1.1.1.2 Administrative & Academic Support Staff......................................................................... 5 1.1.2 Department of Mathematics............................................................................................ 5 1.1.2.1 Academic Staff.............................................................................................................. 5 1.1.2.2 Administrative & Academic Support Staff......................................................................... 6 1.1.3 Department of Statistics................................................................................................. 6 1.1.3.1 Academic Staff.............................................................................................................. 6 1.1.3.2 Administrative & Academic Support Staff......................................................................... 7 1.2 Introduction & Welcome by the Director of School............................................................ 7 1.2.1 School Campuses, Sites and the New School Concept....................................................... 7 1.2.2 Merger of Legacy Institutions......................................................................................... 8 1.2.3 Two Tier Governance Structure....................................................................................... 8 1.2.4 Academic Focus of the School......................................................................................... 8 1.3 School Vision & Mission.................................................................................................. 9 1.3.1 Vision of the School....................................................................................................... 9 1.3.2 Mission of the School..................................................................................................... 9 1.4 School Rules.................................................................................................................. 9 1.5 Minimum Admission Requirements (for the regular programmes).................................... 10 1.5.1 Selection Criteria for New Students............................................................................... 10 1.6 Minimum Admission Requirements and Programme Characteristics (for the extended programmes).................................................................................... 11 1.7 Programme Rules (Undergraduate)............................................................................... 12 1.7.1 Admission Rules........................................................................................................... 12 1.7.2 Progression Rules........................................................................................................ 12 1.7.2.1 Re-Admission of Continuing Students............................................................................ 12 1.7.3 Exit Rules.................................................................................................................... 13 1.7.3.1 Completion Rules......................................................................................................... 13 1.7.3.2 Exclusion Rules............................................................................................................ 13 1.8 Programme Rules (Honours)......................................................................................... 13 1.8.1 Admission Rules........................................................................................................... 13 1.8.2 Progression Rules........................................................................................................ 13 1.8.2.1 Re-Admission of Continuing Students............................................................................ 13 1.8.3 Exit Rules.................................................................................................................... 13 1.8.3.1 Completion Rules......................................................................................................... 13 1.8.3.2 Exclusion Rules............................................................................................................ 14 1.9 Departments and Programmes...................................................................................... 14 1.9.1 Department of Applied Mathematics.............................................................................. 14 1.9.1.1 Information about Department..................................................................................... 14 1.9.1.2 Mission of the Department............................................................................................ 14 1.9.1.3 Goals of the Department.............................................................................................. 14 1.9.1.4 Student Societies in the Department............................................................................. 15 1.9.1.5 Programmes in the Department.................................................................................... 15 1.9.1.5.1 BSc Applied Mathematics.............................................................................................. 15 1.9.1.5.1.1 Entrepeneurship & Professional Development of Students............................................... 15 1.9.1.5.1.2 Career Opportunities.................................................................................................... 15 1.9.1.5.1.3 Purpose of Qualification................................................................................................ 15 1.9.1.5.1.4 Exit Level Outcomes of the Programme......................................................................... 15 1.9.1.5.1.5 Programme Characteristics........................................................................................... 15 1.9.1.5.1.5.1 Academic and Research Orientated Study...................................................................... 15 1.9.1.5.1.5.2 Practical Work............................................................................................................. 16 1.9.1.5.1.5.3 Teaching and Learning Methodology............................................................................. 16 1.9.1.5.1.6 Programme Information............................................................................................... 16 1.9.1.5.1.6.1 Curriculum.................................................................................................................. 16 1.9.1.5.1.6.1.1 Core and Foundation Modules....................................................................................... 16 1.9.1.5.1.6.1.2 Electives...................................................................................................................... 17 1.9.1.5.1.6.1.3 Pre-Requisite Courses.................................................................................................. 18 1.9.1.5.1.6.2 Award Of Qualification.................................................................................................. 19 1.9.1.5.1.6.3 Programme Tuition Fees............................................................................................... 19 1.9.1.5.1.6.4 Articulation.................................................................................................................. 19 1.9.1.5.1.6.5 Core Syllabi of Subjects Offered.................................................................................... 19 1.9.1.5.2 BSc Applied Mathematics (Extended Programme)........................................................... 22 1.9.1.5.2.1 Curriculum.................................................................................................................. 23 1.9.1.5.2.1.1 Core and Foundation Modules....................................................................................... 23 1.9.1.5.2.1.2 Electives...................................................................................................................... 24 1.9.1.5.2.1.3 Pre-Requisite Courses.................................................................................................. 24 1.9.1.5.2.2 Award of Qualification.................................................................................................. 24 SCHOOL OF MATHEMATICAL AND 2 COMPUTATIONAL SCIENCES

1.9.1.5.2.3 Programme Tuition fees................................................................................................ 25 1.9.1.5.2.4 Articulation.................................................................................................................. 25 1.9.1.5.2.5 Core Syllabi Of Courses Offered.................................................................................... 25 1.9.2 Department of Mathematics.......................................................................................... 26 1.9.2.1 Information about Department..................................................................................... 26 1.9.2.2 Mission of the Department............................................................................................ 27 1.9.2.3 Goals of the Department.............................................................................................. 27 1.9.2.4 Student Societies in the Department............................................................................. 27 1.9.2.5 Programmes in the Department.................................................................................... 27 1.9.2.5.1 BSc Mathematics......................................................................................................... 27 1.9.2.5.1.1 Entrepeneurship & Professional Development of Students............................................... 27 1.9.2.5.1.2 Career Opportunities.................................................................................................... 28 1.9.2.5.1.3 Purpose of Qualification................................................................................................ 28 1.9.2.5.1.4 Exit Level Outcomes of the Programme......................................................................... 28 1.9.2.5.1.5 Programme Characteristics........................................................................................... 28 1.9.2.5.1.5.1 Academic and Research Orientated............................................................................... 28 1.9.2.5.1.5.2 Practical Work............................................................................................................. 28 1.9.2.5.1.5.3 Teaching and Learning Methodology............................................................................. 28 1.9.2.5.1.6 Programme Information............................................................................................... 29 1.9.2.5.1.6.1 Curriculum.................................................................................................................. 29 1.9.2.5.1.6.1.1 Core and Foundation Modules....................................................................................... 29 1.9.2.5.1.6.1.2 Electives...................................................................................................................... 30 1.9.2.5.1.6.1.3 Pre-Requisite Courses.................................................................................................. 31 1.9.2.5.1.6.2 Award of Qualification.................................................................................................. 31 1.9.2.5.1.6.3 Programme Tuition Fees............................................................................................... 32 1.9.2.5.1.6.4 Articulation.................................................................................................................. 32 1.9.2.5.1.6.5 Core Syllabi of Subjects Offered.................................................................................... 32 1.9.2.5.2 BSc Mathematics (Extended Programme)...................................................................... 36 1.9.2.5.2.1 Curriculum.................................................................................................................. 36 1.9.2.5.2.1.1 Core and Foundation Modules....................................................................................... 36 1.9.2.5.2.1.2 Electives...................................................................................................................... 36 1.9.2.5.2.1.3 Pre-Requisite Courses.................................................................................................. 37 1.9.2.5.2.2 Core Syllabi Of Courses Offered.................................................................................... 37 1.9.2.5.3 Honours BSc Mathematics............................................................................................ 39 1.9.2.5.3.1 Entrepreneurship & Professional Development of Students.............................................. 39 1.9.2.5.3.2 Career Opportunities.................................................................................................... 39 1.9.2.5.3.3 Purpose of Qualification................................................................................................ 39 1.9.2.5.3.4 Exit Level Outcomes of the Programme......................................................................... 39 1.9.2.5.3.5 Programme Characteristics........................................................................................... 39 1.9.2.5.3.5.1 Academic and Research Orientated............................................................................... 39 1.9.2.5.3.5.2 Practical Work............................................................................................................. 39 1.9.2.5.3.5.3 Teaching and Learning Methodology............................................................................. 39 1.9.2.5.3.6 Programme Information............................................................................................... 40 1.9.2.5.3.6.1 Minimum Admission Requirements................................................................................ 40 1.9.2.5.3.6.2 Selection Criteria for New Students............................................................................... 40 1.9.2.5.3.6.3 Curriculum.................................................................................................................. 40 1.9.2.5.3.6.3.1 Required Modules........................................................................................................ 40 1.9.2.5.3.6.3.2 Courses Offered........................................................................................................... 41 1.9.2.5.3.6.3.3 Pre-Requisite Courses.................................................................................................. 41 1.9.2.5.3.6.4 Award of Qualification.................................................................................................. 41 1.9.2.5.3.6.5 Programme Tuition Fees............................................................................................... 41 1.9.2.5.3.6.6 Articulation.................................................................................................................. 41 1.9.2.5.3.6.7 Core Syllabi of Subjects Offered.................................................................................... 42 1.9.2.5.4 MSc Mathematics......................................................................................................... 44 1.9.2.5.4.1 Entrepreneurship & Professional Development of Students.............................................. 44 1.9.2.5.4.2 Career Opportunities.................................................................................................... 45 1.9.2.5.4.3 Purpose of Qualification................................................................................................ 45 1.9.2.5.4.4 Exit Level Outcomes of the Programme......................................................................... 45 1.9.2.5.4.5 Programme Characteristics........................................................................................... 45 1.9.2.5.4.5.1 Academic and Research Orientated............................................................................... 45 1.9.2.5.4.5.2 Practical Work............................................................................................................. 45 1.9.2.5.4.5.3 Teaching and Learning Methodology............................................................................. 45 1.9.2.5.4.6 Programme Information............................................................................................... 45 1.9.2.5.4.6.1 Minimum Admission Requirements................................................................................ 45 1.9.2.5.4.6.2 Selection Criteria for New Students............................................................................... 45 1.9.2.5.4.6.1 Curriculum.................................................................................................................. 46 1.9.2.5.4.6.2 Available Topics/Areas of Research................................................................................ 46 1.9.2.5.4.6.3 Award of Qualification.................................................................................................. 46 1.9.2.5.4.6.4 Programme Tuition Fees............................................................................................... 46 1.9.2.5.4.6.5 Articulation.................................................................................................................. 46 1.9.2.5.4.6.6 Service Modules offered by the Department................................................................... 47

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1.9.3 Department of Statistics............................................................................................... 47 1.9.3.1 Information about Department..................................................................................... 48 1.9.3.2 Mission of the Department............................................................................................ 48 1.9.3.3 Goals of the Department.............................................................................................. 48 1.9.3.4 Student Societies in the Department............................................................................. 48 1.9.3.5 Programmes in the Department.................................................................................... 48 1.9.3.5.1 BSc Applied Statistical Science...................................................................................... 48 1.9.3.5.1.1 Entrepeneurship & Professional Development of Students............................................... 48 1.9.3.5.1.2 Career Opportunities.................................................................................................... 48 1.9.3.5.1.3 Purpose of Qualification................................................................................................ 48 1.9.3.5.1.4 Exit Level Outcomes of the Programme......................................................................... 48 1.9.3.5.1.5 Programme Characteristics........................................................................................... 50 1.9.3.5.1.5.1 Academic and Research Orientated Study...................................................................... 50 1.9.3.5.1.5.2 Practical Work............................................................................................................. 50 1.9.3.5.1.5.3 Teaching and Learning Methodology............................................................................. 50 1.9.3.5.1.6 Programme Information............................................................................................... 50 1.9.3.5.1.6.1 Curriculum.................................................................................................................. 50 1.9.3.5.1.6.1.1 Core and Foundation Modules....................................................................................... 50 1.9.3.5.1.6.1.2 Electives...................................................................................................................... 51 1.9.3.5.1.6.1.3 Pre-Requisite Courses.................................................................................................. 52 1.9.3.5.1.6.2 Award of Qualification.................................................................................................. 53 1.9.3.5.1.6.3 Programme Tuition Fees............................................................................................... 53 1.9.3.5.1.6.4 Articulation.................................................................................................................. 53 1.9.3.5.1.6.5 Core Syllabi of Subjects Offered.................................................................................... 53 1.9.3.5.2 BSc Applied Statistical Science (Extended Programme)................................................... 56 1.9.3.5.2.1 Curriculum.................................................................................................................. 57 1.9.3.5.2.1.1 Core and Foundation Modules....................................................................................... 57 1.9.3.5.2.1.2 Electives...................................................................................................................... 57 1.9.3.5.2.1.3 Pre-Requisite Courses.................................................................................................. 58 1.9.3.5.2.2 Award of Qualification.................................................................................................. 58 1.9.3.5.2.3 Programme Tuition Fees............................................................................................... 58 1.9.3.5.2.4 Articulation.................................................................................................................. 58 1.9.3.5.2.5 Core Syllabi of Courses Offered..................................................................................... 59 1.9.2.5.3 BSc Honours (Statistical Science).................................................................................. 60 1.9.3.5.3.1 Entrepreneurship & Professional Development of Students.............................................. 60 1.9.3.5.3.2 Career Opportunities.................................................................................................... 61 1.9.3.5.3.3 Purpose of Qualification................................................................................................ 61 1.9.3.5.3.4 Exit Level Outcomes of the Programme......................................................................... 61 1.9.3.5.3.5 Programme Characteristics........................................................................................... 61 1.9.3.5.3.5.1 Academic and Research Orientated............................................................................... 61 1.9.3.5.3.5.2 Practical Work............................................................................................................. 61 1.9.3.5.3.5.3 Teaching and Learning Methodology............................................................................. 61 1.9.3.5.3.6 Programme Information............................................................................................... 61 1.9.3.5.3.6.1 Minimum Admission Requirements................................................................................ 61 1.9.3.5.3.6.2 Selection Criteria for new students................................................................................ 62 1.9.3.5.3.6.1 Curriculum.................................................................................................................. 62 1.9.3.5.3.6.1.1 Core and Foundation Modules....................................................................................... 62 1.9.3.5.3.6.1.2 Electives...................................................................................................................... 62 1.9.3.5.3.6.1.3 Pre-Requisite Courses & Available Electives.................................................................... 62 1.9.3.5.3.6.2 Award of Qualification.................................................................................................. 62 1.9.3.5.3.6.3 Programme Tuition Fees............................................................................................... 62 1.9.3.5.3.6.4 Articulation.................................................................................................................. 63 1.9.3.5.3.6.5 Core Syllabi of Subjects Offered.................................................................................... 63 1.9.3.5.4 MSc (Statistical Science)............................................................................................... 66 1.9.3.5.4.1 Entrepeneurship & Professional Development of Students............................................... 66 1.9.3.5.4.2 Career Opportunities.................................................................................................... 67 1.9.3.5.4.3 Purpose of Qualification................................................................................................ 67 1.9.3.5.4.4 Exit Level Outcomes of the Programme......................................................................... 67 1.9.3.5.4.5 Programme Characteristics........................................................................................... 67 1.9.3.5.4.5.1 Academic and Research Orientated............................................................................... 67 1.9.3.5.4.5.2 Practical Work............................................................................................................. 67 1.9.3.5.4.5.3 Teaching and Learning Methodology............................................................................. 67 1.9.3.5.4.6 Programme Information............................................................................................... 67 1.9.3.5.4.6.1 Minimum Admission Requirements................................................................................ 67 1.9.3.5.4.6.2 Selection Criteria for New Students............................................................................... 68 1.9.3.5.4.6.1 Curriculum.................................................................................................................. 68 1.9.3.5.4.6.2 Available Topics/Areas of Research................................................................................ 68 1.9.3.5.4.6.3 Award of Qualification.................................................................................................. 68 1.9.3.5.4.6.4 Programme Tuition Fees............................................................................................... 68 1.9.3.5.4.6.5 Articulation.................................................................................................................. 68 1.9.3.5.4.6.6 Service Modules Offered by the Department.................................................................. 69 SCHOOL OF MATHEMATICAL AND 4 COMPUTATIONAL SCIENCES

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SCHOOL ADMINISTRATIVE STAFF

Designation Director of School School Officer Secretary 1.1

Name Qualifications Prof. SN Mishra MSc, D.Phil (Allahabad) Vacant Mrs V Ndamase - Nee Maliwa ND: Office Management &Technology (Ect)

Departments Academic and Administrative Staff

1.1.1 Department of Applied Mathematics 1.1.1.1 Academic Staff Designation

Name

Qualifications

Professor Associate Professor Acting HOD/Senior Lecturer Junior Lecturer Parttime Lecturer Part- time Junior Lecturer Part- time

Vacant Dr W Sinkala Dr M Chaisi

BSc (UNZA), MSc (UZ), PhD (UKZN) BSc (NUL), MSc (Wales), PhD (UKZN)

Mr M Makurumure

BSc, BSc (Hons) (NUST)

Mr T F Nkalashe Mr C Kakuli

BSc, BSc (Hons)(Unitra) , MSc(WSU) BSc, BSc (Hons)

1.1.1.2 Administrative & academic support staff None 1.1.2

Department of Mathematics

1.1.2.1 Academic Staff Site: NMD Designation

Name

Qualifications

Professor Professor/Head of Department Acting HOD/ Lecturer Senior Lecturer Senior Lecturer

Prof. SN Mishra Vacant

MSc, D.Phil (Allahabad)

Mrs RM Panicker

BSc, B.Ed, MSc(M.G. Univ. Kerala)

Lecturer Lecturer Junior Lecturer

Mr W Mbava Mrs LS Abraham Mr VB Lucwaba

Vacant Vacant BSc, BSc (Hons),MSc (UZ) BSc,MSc, B.Ed (MG university) BSc, BSc,Hons (Unitra) 5

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Junior Lecturer/Part- Mrs N Thomas time

BSc, BSc,Hons (Unitra)

Site: IBIKA Designation

Name

Qualifications

Acting Site HOD / Senior Lecturer Senior Lecturer Lecturer Lecturer Lecturer Lecturer/Temporary

Mr MS Majova

BSc, HED, BSc (Hons)(Unitra), M. Ed ( Unitra) BSc (Hons)(Unitra), M. Sc ( Unitra) BSc, BSc (Hons)HDE(Unitra) BSc,BSc (Hons)(Unitra) BSc, BSc (Hons),MSc(Unitra) PhD (RU)

Lecturer/Temporary

Mr S Jama

Mr PS Jaca Mrs P Stofile Ms F Tonjeni Dr S Stofile Mr C Kakuli

Site: BC Designation

Name

Qualifications

Acting Site HOD / Lecturer

Mrs J Coetzee

BSc (Hons)(UNISA), BSc(UP),HDE(UNISA), B.Ed(RAU), MSc (Math. Ed) ( UNISA)

Senior Lecturer Lecturer

Vacant Ms M Mbebe

Lecturer/Temporary Lecturer

Mr NE Mbhele Mr M Mofoka

Lecturer Lecturer/Temporary

Ms L Bester Mrs E Oberholster

MBA (NMMU), BSc(RHODES),BSc(HONS)(UWC) BSc (UFH), BSc (Hons) (UFH) (UFH), BSc (HONS)(UFH),NTD MECHENG BSc (UP), BSc (HONS)(UP) MED (RHODES), BCOM (UNISA), BED (UCT), UED, (RHODES), BSC (RHODES) BSc (HONS) (UFH), BSc (UFH)

Lecturer Mr B Mtiya 1.1.2.2 Administrative & academic support staff None 1.1.3 Department of Statistics 1.1.3.1 Academic Staff Designation

Name

Professor/Head of Department Associate Professor

Vacant

Qualifications

Prof KW Binyavanga

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

BSc.Hons, MA (Dar es Salaam), PhD (Stellenbosch) 6

Lecturer

Mr JS Nasila

Senior Lecturer Junior Lecturer Junior Lecturer / Temporary Junior Lecturer/ Part-time

Dr H Moolman Mr L Majeke Mr CE Pokoo-Sonny

BSc (Madras), Post Bacc. Diploma (SFU), M Sc (Simon Fraser) BSc, BSc (Hons) (Unitra), MSc (UFH) BA (Ghana), P.G.D.E (Cape Coast), BSc (Hons) (WSU), MSc (Rhodes) BSc, BSc (Hons) (UFH)

Ms NN Matu

1.1.3.2 Administrative & academic support staff None 1.2

Introduction & Welcome by the Director of School

The School of Mathematical and Computational Sciences at Walter Sisulu University like other such schools in the country and elsewhere, is supposed to play a vital role in serving the current needs of the country. This recognition has to a large extent informed the nature of programmes that are offered in the school. Another factor that has influenced the characteristics of our programmes is the emergence of computers and the “computerisation” of mathematics that has taken place over a number of years. The tremendous impact that this has had on the teaching and research in mathematics cannot be ignored. In this light, the School of Mathematical and Computational Sciences offers programmes that strive to strike a good balance between theory and computation. Currently, the school offers undergraduate and postgraduate programmes in specialised areas of Applied Mathematics, Mathematics and Statistics. These programmes, in particular, the undergraduate programmes, are somewhat interdisciplinary in nature and provide a base from which one can build a career in a mathematical-sciences-related area or proceed to do basic research in Mathematical Sciences. There is an important role that the school plays in many programmes offered in other schools and faculties in that these programmes include courses/modules that are taught by departments in the school. Currently, a large number of students from Engineering, Education and Economic Sciences are serviced by the School of Mathematical and Computational Sciences. 1.2.1

School campuses, sites and the new School concept

The School of Mathematical and Computational Sciences extends over three campuses of the Walter Sisulu University, Mthatha, Butterworth and Buffalo City, and comprises three departments, namely, Applied Mathematics, Mathematics and Statistics. The school offers degree programmes at the levels of BSc, BSc (Hons) and MSc in the respective departments. The following is a summary of programmes that are offered by the School of Mathematical and Computational Sciences.

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Department

Duration Full-time Department BSc Applied Mathematics – ECP* 4yrs of Applied BSc Applied Mathematics 3yrs Mathematics MSc 2yrs Department of BSc Mathematics - ECP* 4yrs Mathematics BSc Mathematics 3yrs Honours BSc Mathematics 1yr MSc Mathematics 2yrs Department of BSc Applied Statistical Science - ECP* 4yrs Statistics BSc Applied Statistical Science 4yrs Honours BSc Applied Statistical Science 1yr MSc Statistical Science 2yrs ECP*: Extended Degree Programme. 1.2.2

Programmes offered

Duration Part-time N/A N/A 4 yrs N/A N/A 2 yrs 4 yrs N/A 2 yrs 2 yrs 4 yrs

Delivery Sites NMD NMD NMD NMD NMD NMD NMD NMD NMD NMD NMD

Merger of legacy institutions

Walter Sisulu University was formed on 1 July 2005 through the merger of Border Technikon, Eastern Cape Technikon and the University of Transkei (Unitra). The business of two of the departments in the School of Mathematical and Computational Sciences, namely, Applied Mathematics and Statistics, is confined to the NMD site, in Mthatha, while that of the department of mathematics extends beyond NMD to Ibika, (Butterworth) Potsdam, Chiselhurst and College Street sites (East London). 1.2.3

Two Tier Governance Structure

All the major programmes offered in the school are located at the Nelson Mandela Drive (NMD) Site. In Buffalo City (Potsdam, Chiselhurst and College Street) and Ibika (Butterworth) the courses offered are essentially service courses to engineering programmes. HODs for the respective departments are stationed at NMD, and are assisted by site HODs at other delivery sites. HODs report to the director of the school, who as academic head oversees the academic programmes within the respective departments. 1.2.4

Academic focus of the School

The academic focus of the school is informed by the recognition of the scarcity in South Africa of skills in Mathematical Sciences. The programmes offered in the school are therefore designed to provide training in various disciplines of mathematical sciences, with the aim of preparing students for placement in jobs requiring a significant tertiary level maturity in Mathematical Sciences, and for further training at a higher level in their areas of specializations.

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

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1.3

School Vision & Mission

1.3.1

Vision of the School

The School of Mathematical and Computational Sciences will be a leading school that offers innovative educational and research programmes in mathematical sciences and their computational applications. 1.3.2

Mission of the School

In pursuit of its vision, the school will: • provide a modern educational environment supported by appropriate technology for instruction and research; • design innovative programmes in teaching and research that will produce highly skilled graduates; • have a caring approach to the teaching of mathematical sciences courses and • create an environment to engage in solving real-world problems and societal challenges; 1.4

School Rules

General Students should note that on registration to study at Walter Sisulu University, they automatically become members of the University and agree to abide by the rules and regulations of Walter Sisulu University as amended from time to time and for which further details are available in the general University prospectus. Class Attendance • • •

All lectures, including tutorials and laboratory work are compulsory. Students should at all times be punctual in attending classes. Lecturers will keep a register of Class Attendance by students, which may be used as part of the assessment of student performance.

Semester Tests, Lab Work and Handing in of Assignments • • •

Students who are absent from semester assessments or who fail to submit assessments before or on the due date, will receive a zero mark for that assessment. If the lecturer is provided with a signed certificate within 7 days after the assessment from a medical practitioner to confirm that he/she was ill and/or incapacitated the assessment will be re-administered. Major semester assessments missed will be re-administered by departmental arrangement.

Course Evaluation Students will be required to complete Evaluation forms on Course Offering & Lecturer for each courses at the end of the course.

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Code of Conduct The following code of conduct forms part of the way the work within the school is envisaged: • That the main focus is for students to study & learn; • that the lecturer and students will take joint responsibility in ensuring that classes are conducted in an environment conducive to learning; • to promote such a learning environment the students & lecturer; • undertake to be respectful to lecturers and other students; • commit themselves to perform the work in a diligent and responsible manner; • understand that students are encouraged to ask questions and get feedback; • undertake to be punctual in attendance of all learning/teaching activities; • undertake to keep venues clean & tidy and agree not to eat or litter inside the classroom and • undertake to take care of the documentation & equipment issued and of the equipment that are used in practicals or in the classroom. 1.5

Minimum Admission Requirements (for the regular programmes)

National Senior Certificate Minimum Accumulated Required NSC Subjects Point Score 29 • Eligibility for admission to a Bachelor’s degree programme • Achievement rating of at least level 4 (50% – 59%) in Mathematics, Physical Sciences, English and two other subjects. Senior Certificate Symbol D in Mathematics and Physical Science at Standard Grade or Symbol E in Mathematics and Physical Science at Higher Grade, Exemption for University entrance. FET Colleges National Certificate: A certificate with C-symbols for at least four subjects including Mathematics, Physical Sciences and language requirements for the Senior Certificate. Recognition of prior learning (RPL) RPL may be used to demonstrate competence for admission to this programme. This qualification may be achieved in part through RPL processes. Credits achieved by RPL must not exceed 50% of the total credits and must not include credits at the exit level. INTERNATIONAL STUDENTS Applications from international students are considered in terms of institutional equivalence reference document submission of international qualification to SAQA for benchmarking in terms of HEQF. MATURE AGE ENDORSEMENT As per General Prospectus Rule G1.6. National Certificate (Vocational) Level 4

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

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• • • •

Must meet NC(V) Level 4 statutory requirements Must obtain 60% in English, Mathematics (not Mathematics Literacy), Life Orientation Must obtain 70% for the following compulsory vocational modules : Systems Analysis and Design, Data Communication and Networking, Computer Programming, Physical Science

1.5.1 Selection Criteria for New Students Selection of new students will be based on scores in Mathematics, English and Physical Science. Students with scores in these subjects higher than the minimum requirements will be selected into the programme. Students who are not selected into this programme may be offered places in the extended programme if they meet the admission requirements there. 1.6

Minimum Admission Requirements and Programme Characteristics (for the extended programmes)

Name of BSc (Extended Programme) Programme Minimum number of 480 credits Delivery Site(s) NMD Duration of A minimum of four years of fulltime study Programme Programme Outcomes Critical Outcomes The learner will be able to: Understand the main mathematical concepts and techniques. Develop a culture of critical and analytical thinking that may be required in problem solving including the mathematical modeling and formulation of real-world problems.

Accreditation & Quality Assurance

Vocational Outcomes After the successful completion of the programme the learner will be able to utilize the acquired skills in various disciplines such as Science and Engineering, Economic Sciences, Social Sciences and Humanities. CHE, HEQC & SAQA accredited

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Admission Requirements

1. Matriculation:National Senior Certificate: Same as for the regular programme. OR Senior Secondary School Certificate: Same as for the regular programme. 2. Standardized Assessment Test for Access and Placement (SATAP): The candidate is tested in Mathematics, Science & English. The tests scores may be used for access and placement. Progression Rules • Refer to Section 1.7.2.1. below. Graduation Requirements In order to meet the minimum requirements to complete the Programme the following criteria must be satisfied: • Complete all core modules at all levels and permitted electives with a total value of at least 480 credits. Each fulltime study-year should comprise a minimum of 120 credits. • The minimum number of credits that must be completed at Walter Sisulu University must not be less than 50% of the total number of credits required for the completion of the programme. All core modules at level three must be completed at Walter Sisulu University. 1.7

Programme Rules (Undergraduate)

In order to be allowed to proceed to the next level, the following criteria must be satisfied: • All core modules must be passed at the current level. 1.7.1

Admission Rules

Admission into the programme is contingent upon: • Meeting the minimum requirements for admission to the programme; • selection into the programme, (selection is limited by enrolment limits); • Further, • admission is on a first come first served basis for students who qualify in terms of selection criteria; • not more than 50% of the credits from other institutions will be recognised and • all exit level courses will only be exempted under extraneous conditions. See also General Prospectus Rules. 1.7.2 Progression Rules 1.7.2.1 Re-Admission of Continuing Students •

Students should take note of the Institutional rules G7-G11 on re-admission of students to undergraduate programme. As provided under institutional rules G8.1, 8.2, 9.1 & 9.2, the school has set the following criteria for re-admission. • A student that progresses at a slower rate set out below, will be refused further reSCHOOL OF MATHEMATICAL AND 12 COMPUTATIONAL SCIENCES

admission on the grounds of “poor academic performance’’. 3 Year B Sc (mainstream) At the end of academic period(year)

1

2

3

4

5

Minimum credits students must have obtained

72

144

216

288

360

4 Year B Sc (extended programme) At the end of academic period(year)

1

2

3

4

5

6

Minimum credits students must have obtained

80

160

240

320

400

480



A student who completes all core modules and pre requisite modules will progress from one level to the next.

1.7.3

Exit Rules

1.7.3.1 Completion Rules • • • •

All courses and modules in the curriculum must be completed. A minimum of 120 credits must be earned at each level of the curriculum. A minimum total of 360 credits must be completed for the three year programs. A minimum total of 480 credits must be completed for the four year programs.

1.7.3.2 Exclusion Rules Refer to Section 1.7.2.1. 1.8

Programme Rules (Honours)

1.8.1

Admission Rules

Admission into the programme is contingent upon: • Meeting the minimum requirements for admission to the programme; • selection into the programme, (selection is limited by enrolment limits); • Further, admission is on a first come first served basis for students who qualify in terms of selection criteria. See also General Prospectus Rules. 1.8.2 Progression Rules 1.8.2.1 Re-Admission of Continuing Students • •

Refer to the institutional rules on re-admission of students previously admitted as contained in the revised examination policy and the institution prospectus. A student who fails the same course twice is not allowed to re-register for the same course.

13

2014

PROSPECTUS

1.8.3

Exit Rules

1.8.3.1 Completion Rules All courses and modules in the curriculum must be completed. A minimum of 120 credits must be earned at each level of the curriculum. 1.8.3.2 Exclusion Rules The maximum period for the degree programme is three years. See also Rules in the General Prospectus. 1.9

Departments and Programmes

1.9.1

Department of Applied Mathematics

1.9.1.1 Information about Department Applied mathematics is in a sense the cornerstone of modern science as it is concerned with the use of mathematical techniques to solve real-world problems. Consistent with this philosophy, the BSc programme offered in the Department of Applied Mathematics is designed to provide the necessary foundation in mathematics and to introduce students to the application of mathematics in the modeling and solution of real-world problems. More information on the BSc programme is presented below. Department

Programmes offered

Applied Mathematics Applied Mathematics Applied Mathematics

BSc Applied Mathematics - ECP BSc Applied Mathematics MSc

Duration (Full-time) 4 3 2

Delivery Sites NMD NMD NMD

1.9.1.2 Mission of the Department The mission of the Department of Applied Mathematics includes: • Creating a mathematically rich environment for the development of sufficiently sophisticated scientists, engineers and teachers of mathematics; • conducting and promoting research that addresses the local, regional as well as national priorities; • popularizing mathematics through innovative teaching methods and constant communication with other interfacing departments and • continually streamlining our programmes to align them with the demands of industry and commerce. 1.9.1.3 Goals of the Department The goals of the Department of Applied Mathematics are: • To produce quality graduates capable of dynamic participation in the economic and environmental development of the region and beyond; • to work closely with our community and attempt to solve some of their problems and SCHOOL OF MATHEMATICAL AND 14 COMPUTATIONAL SCIENCES



ensure that the programmes are always relevant to their needs and through a commitment to service excellence, staff development and the maximum use of human and other resources, the Department of Applied Mathematics strives to unite students, staff and employers in the common goal of improving the quality of life of our community.

• 1.9.1.4 Student Societies in the Department Science Students Society 1.9.1.5 Programmes In The Department 1.9.1.5.1 BSc Applied Mathematics 1.9.1.5.1.1

Entrepeneurship & Professional Development of Students

Mathematics is a scarce skill in South Africa and is crucial to the scientific and technological development that leads to economic development of the country. In view of this, the long term plan of the department envisages the establishment of a linkage between the department and industry and commerce. 1.9.1.5.1.2

Career Opportunities

A Bachelor of Science degree in Applied Mathematics will prepare the student for jobs in statistics, actuarial sciences, mathematical modelling, cryptography, for teaching, as well as postgraduate training leading to a research career in a discipline of Mathematical Sciences. A strong background in Applied Mathematics is also necessary for research in many areas of computer science, social science, and engineering. 1.9.1.5.1.3

Purpose of Qualification

To provide basic mathematical knowledge tailored for application in the solution of technical problems in the marketplace, and for further training at a higher level in various specializations of Mathematical Sciences. 1.9.1.5.1.4

Exit Level Outcomes of the Programme

A BSc Applied Mathematics graduate should: • Demonstrate knowledge and understanding of basic concepts and principles in mathematics; • have a sound mathematical base for further training in mathematics and/or other fields of study that require a mathematical foundation; • develop a culture of critical and analytical thinking and be able to apply scientific reasoning to societal issues; • demonstrate ability to write mathematics correctly; • be able to manage and organize own learning activities responsibly and • be able to demonstrate ability to solve mathematical problems.

15

2014

PROSPECTUS

1.9.1.5.1.5

Programme Characteristics

1.9.1.5.1.5.1

Academic and Research Orientated Study

The degree programme is designed to provide basic mathematical knowledge tailored for application in the solution of technical problems in the marketplace, and for further training at a higher level in various specializations of mathematical sciences. The courses in this programme are developed co-operatively using inputs from internal and external academic sources on a continuous basis. 1.9.1.5.1.5.2

Practical Work

Practical work in tutorials and computer laboratories provides the practical experience and the development of computing and research skills that will form the base for future work, academic and research engagement. 1.9.1.5.1.5.3

Teaching and Learning Methodology

Learning activities include lectures, tutorials, practicals in which independent study are integrated. 1.9.1.5.1.6

Programme Information

The entire programme is designed to consist of at least 50% of the credits from Mathematics and/or Applied Mathematics. See Section 1.5 for the Minimum Admission Requirements and Section 1.7 for Programme Rules. 1.9.1.5.1.6.1

Curriculum

Student must take all the Core modules and Foundational modules at each level. Relevant electives for which the student has the required pre-requisites must then be chosen so that the student has a minimum of 120 credits at each level. However, no student may register for more than 128 credits in any given academic year. 1.9.1.5.1.6.1.1 Core and Foundation Modules Level 1 Module Name Core Modules Precalculus & Calculus I Introduction to Linear & Vector Alg. Precalculus & Calculus II Linear Programming & Applied Computing Foundation Modules Computer Literacy Communication Skills Total core credits SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

16

Code

Credits

Semester

MAT1101

16

1

APM1101 MAT1201 APM1201

16 16 16

1 2 2

CLT1101 EDU1001

8 8 80

1 1 1&2

Electives required Total credits Level 2 Module Name Multivariate Calculus Ordinary Differential Equations Numerical Analysis I Real Analysis I Linear Algebra I Eigenvalue Problems and Fourier Analysis Total core credits Electives required Total credits Level 3 Module Name Numerical Methods Complex Analysis Mathematical Programming Linear Algebra II Total core credits Electives required Total credits

40 120

1&2 1&2

Code MAT2101 MAT2201 APM2101 MAT2102 MAT2202 APM2201

Credits 8 8 16 8 8 16 64 56 120

Semester 1 1 1 2 2 2 1&2 1&2 1&2

Code APM3101 MAT3202 APM3201 MAT3102

Credits 16 16 16 16 64 56 120

Semester 1 2 2 1 1&2 1&2 1&2

Code CHE1101 CSI1101 CSI1102 PHY1101 STA1101 CHE1201 CSI1201 PHY1202 STA1202

Credits 16 8 8 16 16 16 8 16 16

Semester First First First First First Second Second Second Second

Code APM2202 CHE2102 CHE2105 CSI2101

Credits 16 16 16 14

Semester 2 1 First First

1.9.1.5.1.6.1.2 Electives Level 1 Module Name General Chemistry I Information Systems and Applications Problem Solving and Programming General Physics I Probability & Distribution Theory I General Chemistry I Problem Solving and Programming General Physics II Probability & Statistical Inference I Level 2 Module Name Mechanics I Analytical Chemistry II Physical Chemistry II Programming in JAVA 17

2014

PROSPECTUS

Mechanics & Waves Probability & Distribution Theory II Inorganic Chemistry II Organic Chemistry II Thermodynamics and Modern Physics Operating Systems Statistical Inference II Level 3 Module Name Inorganic Chemistry III Organic Chemistry III Introduction to Artificial Intelligence Software Engineering I Electromagnetism and Quantum Mechanics Linear Models Analytical Chemistry III Physical Chemistry III Environmental Chemistry – 2003 Data Management Software Engineering II Statistical Mechanics and Solid State Physics Sampling Theory

PHY2101 STA2101 CHE2203 CHE2204 PHY2202 CSI2201 STA2202

16 16 16 16 16 14 16

First First Second Second Second Second Second

Code CHE3103 CHE3104 CSI3101 CSI3102 PHY3101 STA3101 CHE3202 CHE3205 CHE3207 CSI3201 CSI3202 PHY3202 STA3203

Credits 16 8 14 14 24 16 16 16 12 14 14 24 16

Semester First First First First First First Second Second Second Second Second Second Second

1.9.1.5.1.6.1.3 Pre-Requisite Courses Code

MAT2101

Course Name Level I Precalculus & Calculus I Introduction to Linear & Vector Alg. Precalculus & Calculus II Linear Programming & Applied Computing Level II Multivariate Calculus

MAT2201

Ordinary Differential Equations

APM2101

Numerical Analysis I

MAT2102

Real Analysis I

MAT2202

Linear Algebra I

MAT1101 APM1101 MAT1201 APM1201

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

18

Pre-Requisite FACULTY FACULTY FACULTY FACULTY

admission admission admission admission

requirements requirements requirements requirements

Precalculus & Calculus I, Precalculus Calculus II Precalculus & Calculus I, Precalculus Calculus II All Level I APM courses, MAT1101, MAT1201 Precalculus & Calculus I, Precalculus Calculus II Precalculus & Calculus I, Precalculus Calculus II

& &

& &

APM2201

MAT3101

Eigenvalue Problems and Fourier Analysis Mechanics I Level III Real Analysis II

MAT3102

Linear Algebra II

APM3101 MAT3201

Numerical Methods Abstract Algebra

MAT3202

Complex Analysis

APM3201

Mathematical Programming

APM2202

1.9.1.5.1.6.2

All Level I APM courses , MAT1101, MAT1201, MAT2201 All Level I APM courses, MAT2101 Multivariate Calculus, Linear Algebra I Multivariate Calculus, Linear Algebra I APM2101, APM2201 Multivariate Calculus, Linear Algebra I Multivariate Calculus, Linear Algebra I APM2101, APM2201

Real Analysis I, Real Analysis I,

Real Analysis I, Real Analysis I,

Award of Qualification

The qualification will be awarded after the satisfaction of the programme requirements, including completion of 360 credits with a minimum of 120 credits obtained at each level. See also Rule G12 of the General Prospectus. 1.9.1.5.1.6.3

Programme Tuition Fees

Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition fees, application fees, registration fees, late registration-fees and other student fees. 1.9.1.5.1.6.4

Articulation

Vertical Vertical Articulation is possible with: BSc Hons Mathematics and BSc Hons Applied Mathematics, NQF Level 8 Horizontal Within WSU Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc Applied Statistical Science. Other Universities Horizontal Articulation is possible with NQF Level 7 qualifications offered by other institutions, subject to the relevant institution’s admission requirements.

19

2014

PROSPECTUS

1.9.1.5.1.6.5

Core Syllabi of Courses Offered

APM1101: Introduction to Linear and Vector Algebra Module Code APM1101 Lectures per week

Module Name NQF Level Credits 5 16 Pracs per week Tutorials per week Number of weeks

4 x 50 min Content / Syllabus

Assessment

1 x 100 min

Semester 1 Notional hours

13

Iantroduction to Systems of Linear Equations, Gaussian Elimination, Matrices and Matrix Operations, Inverses Systems of Equations and Invertibility, Determinant, Cramer’s rule, Eigenvalues and Eigenvectors, LU-Decomposition, Cryptography, Sets and Set Operations, The Fundamental Counting Principle, Permutations, Combinations, The Binomial Theorem, Basic Concepts of Probability, Probability Models, Vectors and Vector Operations, The Dot Product, The Cross Product, Applications to Mechanics. Laboratory Work on Vectors and Linear Algebra with MATLAB. Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

APM1201: Linear Programming Module Code APM1201 Lectures per week

Module Name Pracs per week

4 x 50 min Content / Syllabus

Assessment

NQF Level Credits 5 16 Tutorials per week Number of weeks 1 x 100 min

Semester 2 Notional hours

13

Boolean Algebra: Introduction Two-Terminal Circuit Series-Parallel and Bridge Circuits Postulates of Switching Circuits Boolean Identities Identity Elements, Inverses and Cancellations. Linear programming: Introduction, LP Models, The Diet Problem, The Work-Scheduling Problem, A Capital Budgeting Problem, Short-term Financial Planning, Blending Problems, Production Process Models, Multi-period Decision Problems: An Inventory Model, Multi-period Financial Models, Multi-period Work Scheduling, The Graphical Method, The Simplex Method – Maximization, The Simplex Method – The Dual, The Simplex Method – Mixed Constraints Applied computing. Introduction to MATLAB. Laboratory Work with MATLAB involving manipulating Matrices, Linear Algebra, Linear Programming. Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

20

APM2101: Numerical Analysis I Module Code APM2101 Lectures per week

Module Name Pracs per week

4 x 50 min Content / Syllabus

Assessment

NQF Level Credits 6 16 Tutorials per week Number of weeks 1 x 100 min

Semester 1 Notional hours

13

Introduction to numerical analysis: Iterative Methods, Programming with MATLAB, Interpolation and polynomial approximation: Difference Operators, Constructing Difference Tables using MATLAB, Lagrange Polynomial Interpolation, Hermite Interpolation, Divided Differences, Hermite Revisited, Error Estimation, Numerical differentiation and integration: Differentiation, integration, Newton-Cotes Formulae, Composite Integration. Initial value problems, Existence Theorem, Euler Method, Higher Order Taylor Methods, Runge-Kutta Methods, Midpoint Rule, Higher Order R-K Methods, Multistep Methods, Adams-Bashforth Technique, Adams-Moulton Technique, Predictor Corrector Method Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

APM2201: Eigen-Value Problems and Fourier Analysis Module Code Module Name APM2201 Lectures per week Pracs per week 4 x 50 min

NQF Level 6 Tutorials per week 1 x 100 min

Credits Semester 16 1 Number of weeks Notional hours 13

Content / Syllabus Fourier Series: Orthogonality & Normality (Orthonomality) of trigonometric functions, Odd & Even functions, Trigonometric series: Full range & Half range Fourier Series, Parseval Identity. Partial Differential Equations: How initial & boundary value problem relate to (PDEs),Wave Equation, Heat Equation, Laplace Equation, How the separation of variables technique leads (in the simplest examples) to Fourier Series. Eigenvalue Problems: Sturm-Liouville Equation eigenfuctions & corresponding eigenvalues of Sturm-Liouville problem, Sturm-Liouville problem for equation y”+ly = 0 (eigenvalues & eigenfunctions), Orthogonality of SturmLiouville eigenfunctions, Series solution Ordinary Differential Equations: Bessel, Legendre, Hermite and associated functions, Solution of Bessell Equation, recurrence relations, Solution of Legendre equation: Legendre polynomials & Rodrigues formulae, Green formulae and application to Laplace equation, Vibration of rectangular & circular membrane, Fourier integral & transformation Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

21

2014

PROSPECTUS

APM2202: Mechanics I Module Code APM2202 Lectures per week

Module Name Mechanics I Pracs per week

4 x 50 min Content / Syllabus

Assessment

NQF Level Credits Semester 6 16 1 Tutorials per week Number of weeks N o t i o n a l hours 1 x 100 min 13

Particle kinematics in three dimensions. Curvilinear coordinates; spherical and cylindrical. Newton’s law of motion. Conservation of energy. Gravitational and potential theory. Conservation of linear momentum. Collisions. Conservation of angular momentum. Central forces and planetary motion. Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

APM3101: Numerical Methods Module Code APM3101 Lectures per week

Module Name Pracs per week

4 x 50 min Content / Syllabus

Assessment

NQF Level 7 Tutorials per week 1 x 100 min

Credits Semester 16 1 Number of weeks N o t i o n a l hours 13

Laplace & Poisson equations: Elliptic, Heat equations-Parabolic, Wave equations-Hyperbolic. Finite difference method: Replacement of partial derivatives in a given equation by corresponding finite difference quotients. Further treatment of the patterns lead us to: Gauss-Seidel Method for Elliptic case. Crank Nicholson Method for Parabolic equations. Present Numerical Method for Parabolic equations. The Finite Element Method (introduction). Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

APM3201: Mathematical Programming Module Code Module Name APM3201 Lectures per week Pracs per week

NQF Level 7 Tutorials per week

Credits 16 Number of weeks

4 x 50 min

1x 100 min

13

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

22

Semester 2 Notional hours

Content / Syllabus Linear programming: Basic ideas and concepts of program formulation, Simplex method, Dual problem solution & its relation to the primal. Nonlinear programming (NLP) background involves classification of problems/programs according to: Minimization of unconstrained NLPs, Linearly constrained NLPs that include a special subclass of quadratic programs concerned with minimization of quadratic functions, Objective function having appropriate convexity property. Solution Methods: Lagrangian function with associated multipliers and conditions, KuhnTucker conditions for inequality constrained minimization problems. Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%. 1.9.1.5.2

BSc Applied Mathematics (Extended Programme):BSCEA

The first 2 years of the BSc Applied Mathematics (Extended Programme) are equivalent to the first year of the BSc Applied Mathematics programme. In the last two years of the BSc Applied Mathematics (Extended Programme) the students follow the BSc Applied Mathematics programme from second year. At each of the years, 1, 2, 3 & 4, a student must accumulate at least 120 credits towards the total graduation credits. All the core modules (and foundation modules in the case of Level 1) must be taken at each Level. The remaining credits to satisfy the credit requirements at the respective level must be accumulated from the electives. See Section 1.6 for Admission Requirements and Programme and Characteristics. 1.9.1.5.2.1



1.9.1.5.2.1.1

Curriculum Core and Foundation Modules

Level 1a (BSCEA) Module Name Core Mathematical Methods I Mathematical Methods II Integrated Mathematics I Integrated Mathematics II Foundation Computer Science Fundamentals Academic Literacy I Introduction to Programming I Academic Literacy II Life Skills Level 1b ( BSCEA) Module Name Core Mathematical Methods III

Code

Credits

Semester

APM1111 APM1212 MAT1111 MAT1212

16 16 16 16

1 2 1 2

CSI1111 ACL1111 CSI1212 ACL1212 LSK1012

16 8 16 8 8

1 1 2 2 2

Code

Credits

Semester

APM1113

16

1

23

2014

PROSPECTUS

Mathematical Methods IV APM1214 Integrated Mathematics III MAT1113 Integrated Mathematics IV MAT1214 Foundation Introduction to Computer Architecture CSI1113 Introduction to Programming II CSI1214 Total core credits Electives required Total credits Level 3 – same as level 2 of BSc 3 year programme Module Name Code Multivariate Calculus MAT2101 Ordinary Differential Equations MAT2201 Numerical Analysis I APM2101 Real Analysis I MAT2102 Linear Algebra I MAT2202 Eigenvalue Problems and Fourier Analysis APM2201 Total core credits Electives required Total credits Level 4 – same as level 3 of BSc 3 year programme Module Name Code Numerical Methods APM3101 Complex Analysis MAT3202 Mathematical Programming APM3201 Linear Algebra II MAT3102 Total core credits Electives required Total credits 1.9.1.5.2.1.2

16 16 16

2 1 2

16 16 96 24 120

1 2 1&2 1&2 1&2

Credits 8 8 16 8 8 16 64 56 120

Semester 1 1 1 2 2 2 1&2 1&2 1&2

Credits 16 16 16 16 64 56 120

Semester 1 2 2 1 1&2 1&2 1&2

Electives

Level 1a (BSCEA) – An elective cannot be taken, presently, at this year because of exceeding credits Module Name Code Credits Semester Extended General Chemistry I CHE1111 16 1 Extended General Physics II PHY1212 16 2 Extended Organic and Physical Chemistry I CHE1212 16 2 Level 1b (BSCEA) Extended General Physics III PHY1113 16 1 Extended General Chemistry II CHE1113 16 1 Probability & Distribution theory I STA1101 16 1 SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

24

Extended General Physics IV Extended Organic and Physical Chemistry II Statistical Inference I 1.9.1.5.2.1.3 Course Code APM1111 APM1212 APM1113 APM1214 MAT1111 MAT1212 MAT1113 MAT1214 1.9.1.5.2.2

PHY1214 CHE1214 STA1202

16 16 16

2 2 2

Pre-Requisite Courses Course Name Mathematical Methods I Mathematical Methods II Mathematical Methods III Mathematical Methods IV Integrated Mathematics I Integrated Mathematics II Integrated Mathematics III Integrated Mathematics IV

Pre-Requisite Faculty admission requirements Faculty admission requirements Faculty admission requirements Faculty admission requirements Faculty admission requirements FACULTY admission requirements MAT1111 MAT1212

Award of Qualification

The qualification will be awarded after the satisfaction of the programme requirements, including completion of 360 credits with a minimum of 120 credits obtained at each level. See also Rule G12 of the General Prospectus. 1.9.1.5.2.3

Programme Tuition Fees

Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition fees, application fees, registration fees, late registration-fees and other student fees. 1.9.1.5.2.4

Articulation

Vertical Vertical Articulation is possible with: BSc Hons Mathematics and BSc Hons Applied Mathematics, NQF Level 8 Horizontal Within WSU Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc Applied Statistical Science. Other Universities Horizontal Articulation is possible with NQF Level 7 qualifications offered by other institutions, subject to the relevant institution’s admission requirements.

25

2014

PROSPECTUS

1.9.1.5.2.5

Core Syllabi of Courses Offered

APM1111: Mathematical Methods I Module Code

Module Name

APM1111 Lectures per week 2 x 50 min

5 16 1 Pracs per week Tutorials per week Number of weeks Notional hours 0 1 x 50 min 13 160

Content / Syllabus

Coordinate Systems: Review of Coordinate Systems in 2 and 3 dimensions Vectors: Introduction to vectors, Vector Operations, The Dot Product, The Cross Product, Applications to Coordinate Geometry and Mechanics Laboratory Work on Vectors with MATLAB Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

Assessment

NQF Level

Credits

Semester

APM1212: Mathematical Methods II Module Code Module Name NQF Level Credits Semester APM1212 5 16 2 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 0 1 x 50 min 13 160 Content / Syllabus Matrix Theory: Matrices and Matrix Operations, Determinants, Inverses. Systems of Linear Equations: Introduction to Systems of Linear Equations, Gaussian Elimination, Gauss-Jordan Elimination, Systems of Equations and Invertibility, Laboratory Work on Linear Algebra with MATLAB Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%. APM1113: Mathematical Methods III Module Code Module Name NQF Level Credits Semester APM1113 5 16 2 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 0 1 x 50 min 13 160 Content / Syllabus Sets: Set Operations, De Morgan’s laws, Power Set, Cartesian Products, Indexed Families of Sets, Laws of Algebra of Sets The Fundamental Counting Principle, Permutations, Combinations, The Binomial Theorem, The Principle of Mathematical Induction. Logic: Logical Operations and Truth Tables, Tautologies and Contradictions, Logical Equivalence. Boolean algebra: Boolean Polynomials, Introduction to Two-Terminal Circuit Series-Parallel and Bridge Circuits, Postulates of Switching Circuits, Boolean Identities, Identity Elements, Inverses, and Cancellations. Laboratory Work on Discreet Mathematics with MATLAB SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

26

Assessment

Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

APM1214: Mathematical Methods IV Module Code Module Name NQF Level Credits APM1214 5 16 Lectures per week Pracs per week Tutorials per week Number of weeks 2 x 50 min 0 1 x 50 min 13 Content/ Syllabus

Assessment

1.9.2

Semester 2 Notional hours 160

Linear programming: Introduction, LP Models, The Diet Problem, The Work- Scheduling Problem, A Capital Budgeting Problem, Short-term Financial Planning, Blending Problems, Production Process Models, Multi-period Decision Problems: An Inventory Model, Multi-period Financial Models, Multi-period Work Scheduling, The Graphical Method, The Simplex Method – Maximisation, The Simplex Method – The Dual, The Simplex Method – Mixed Constraints Laboratory Work on Linear Programming with MATLAB Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

Department of Mathematics

1.9.2.1 Information about Department The Department of Mathematics strives towards improving its leadership role in the training of mathematicians who will contribute to the development of the country. It promotes excellence in appropriate research and offers career orientated degree programmes. The Department offers programmes at the Mthatha Campus (Nelson Mandela Drive delivery site), and service courses at three campuses (Mthatha, Butterworth and Buffalo City) and five delivery sites (Nelson Mandela Drive, Ibika, Potsdam, Chiselhurst and College Street). The following is a summary of programmes that are offered by the Department of Mathematics. Department Department of Mathematics

1.9.2.2

Programmes offered BSc Mathematics (ECP)-BSCME BSc Mathematics-BSCM BSc Hons Mathematics-BSM MSc Mathematics

Duration 4yrs 3yrs 1yrs 2yrs

Delivery Sites NMD NMD NMD NMD

Mission of the Department

The mission of the Department of Mathematics includes: • Creating mathematically rich environment for the development of sufficiently sophisticated scientists, engineers and teachers of mathematics. • Conducting and promoting research that addresses the local, regional as well as national 27

2014

PROSPECTUS

• •

priorities. Popularizing mathematics through innovative teaching methods and constant communication with other interfacing departments. Continually streamlining our programmes to align them with the demands of industry and commerce.

1.9.2.3

Goals of the Department

The goals of the Department of Mathematics are: • To produce quality graduates capable of dynamic participation in the economic and environmental development of the region and beyond. • Working closely with our community attempt to solve some of the problems and ensure that the programmes are always relevant to their needs. • Through a commitment to service excellence, staff development and the maximum use of human and other resources, the Department of Mathematics strives to unite students, staff and employers in the common goal of improving the quality of life of our community. 1.9.2.4

Student Societies in the Department

Science students society 1.9.2.5

Programmes in the Department

1.9.2.5.1

BSc Mathematics (BSCM)

1.9.2.5.1.1

Entrepeneurship & Professional Development of Students

Mathematics is a scarce skill in South Africa and is crucial to the scientific and technological development that leads to economic development of the country. In view of this, the long term plan of the department envisages the establishment of a linkage between the department and industry and commerce. 1.9.2.5.1.2

Career Opportunities

A Bachelor of Science degree in mathematics will prepare the student for jobs in statistics, actuarial sciences, mathematical modeling, and cryptography; for teaching; as well as postgraduate training leading to a research career in mathematics. A strong background in mathematics is also necessary for research in many areas of computer science, social science, and engineering 1.9.2.5.1.3

Purpose of Qualification

To provide basic mathematical knowledge needed for placement in jobs requiring a significant amount of mathematical maturity, and for further training at a higher level in various specializations of mathematics. 1.9.2.5.1.4

Exit Level Outcomes of the Programme

A BSc Applied Mathematics graduate should: • demonstrate knowledge and understanding of basic concepts and principles in mathematics, • have a sound mathematical basis for further training in mathematics and/or other fields of study that require a mathematical foundation, • develop a culture of critical and analytical thinking and be able to apply scientific reasoning SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

28

• •

to societal issues, demonstrate ability to write mathematics correctly, be able to manage and organize own learning activities responsibly, be able to demonstrate ability to solve mathematical problems.

• 1.9.2.5.1.5

Programme Characteristics

1.9.2.5.1.5.1

Academic and Research Orientated

The programme is mainly academic and research orientated because academic study is combined with related practical work aimed at developing more conceptual mathematical than computational outcomes. The courses in this programme are developed co-operatively using inputs from internal and external academic sources on a continuous basis. 1.9.2.5.1.5.2

Practical Work

Practical work in tutorials and computer laboratories provides the practical experience and the development of computing and research skills that will form the basis of future work, academic and research engagement. 1.9.2.5.1.5.3

Teaching and Learning Methodology

Learning activities include lectures, tutorials, practicals in which in which independent study are integrated. 1.9.2.5.1.6

Programme Information

The programme is designed to consist of at least 50% of the credits from Mathematics and/or Applied Mathematics. See Section 1.5 for the Minimum Admission Requirements and Section 1.7 for Programme Rules. 1.9.2.5.1.6.1

Curriculum

1.9.2.5.1.6.1.1 Core and Foundation Modules Level 1 Module Name Core Precalculus & Calculus I Introduction to Linear & Vector Alg. Precalculus & Calculus II Linear Programming & Applied Computing Foundation Computer Literacy Communication Skills Total credits Level 2 Module Name Multivariate Calculus 29

Code

Credits

Semester

MAT1101 APM1101 MAT1201 APM1201

16 16 16 16

First First Second Second

CLT1101 EDU1001

8 8 80

First First

Code MAT2101

Credits 8

Semester First

2014

PROSPECTUS

Ordinary Differential Equations Numerical Analysis I Real Analysis I Linear Algebra I Eigenvalue Problems and Fourier Analysis Total credits Level 3 Module Name Real Analysis II Linear Algebra II Numerical Methods Abstract Algebra Complex Analysis Mathematical Programming Total credits

MAT2201 APM2101 MAT2102 MAT2202 APM2201

8 16 8 8 16 64

First First Second Second Second

Code MAT3101 MAT3102 APM3101 MAT3201 MAT3202 APM3201

Credits 16 16 16 16 16 16 96

Semester First First First Second Second Second

Code CHE1101 CSI1101 CSI1102 PHY1101 STA1101 CHE1201 CSI1201 PHY1202 STA1202

Credits 16 8 8 16 16 16 8 16 16 40

Semester First First First First First Second Second Second Second

Code APM2202 CHE2102 CHE2105 CSI2101 PHY2101 STA2101 CHE2203 CHE2204 PHY2202 CSI2201

Credits 16 16 16 14 16 16 16 16 16 14

Semester Second First First First First First Second Second Second Second

1.9.2.5.1.6.1.2 Electives Level 1 Module Name General Chemistry I Information Systems and Applications Problem Solving and Programming General Physics I Probability & Distribution Theory I General Chemistry I Problem Solving and Programming General Physics II Probability & Statistical Inference I Minimum total credits Level 2 Module Name Mechanics I Analytical Chemistry II Physical Chemistry II Programming in JAVA Mechanics & Waves Probability & Distribution Theory II Inorganic Chemistry II Organic Chemistry II Thermodynamics and Modern Physics Operating Systems SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

30

Statistical Inference II Minimum total credits Level 3 Module Name Inorganic Chemistry III Organic Chemistry III Introduction to Artificial Intelligence Software Engineering I Electromagnetism and Quantum Mechanics Linear Models Analytical Chemistry III Physical Chemistry III Environmental Chemistry – 2003 Data Management Software Engineering II Statistical Mechanics and Solid State Physics Sampling Theory Minimum total credits

STA2202

16 56

Second

Code CHE3103 CHE3104 CSI3101 CSI3102 PHY3101 STA3101 CHE3202 CHE3205 CHE3207 CSI3201 CSI3202 PHY3202 STA3203

Credits 16 8 14 14 24 16 16 16 12 14 14 24 16 24

Semester First First First First First First Second Second Second Second Second Second Second

1.9.2.5.1.6.1.3 Pre-Requisite Courses Code

Course Name Level 1

Pre-Requisite

MAT1101 APM1101 MAT1201 APM1201

FACULTY admission requirements FACULTY admission requirements FACULTY admission requirements Introduction to Linear & Vector Algebra

MAT2101

Precalculus & Calculus I Introduction to Linear & Vector Alg. Precalculus & Calculus II Linear Programming & Applied Computing Level 2 Multivariate Calculus

MAT2201

Ordinary Differential Equations

APM2101

Numerical Analysis I

MAT2102

Real Analysis I

MAT2202

Linear Algebra I

APM2201

Eigenvalue Problems and Fourier Analysis Mechanics I

APM2202

31

Precalculus & Calculus I, Precalculus Calculus II Precalculus & Calculus I, Precalculus Calculus II All Level I APM courses, MAT1101, MAT1201 Precalculus & Calculus I, Precalculus Calculus II Precalculus & Calculus I, Precalculus Calculus II All Level I APM courses , MAT1101, MAT1201, MAT2201 All Level I APM courses, MAT2101

& &

& &

2014

PROSPECTUS

MAT3101

Level 3 Real Analysis II

MAT3102

Linear Algebra II

APM3101 MAT3201

Numerical Methods Abstract Algebra

MAT3202

Complex Analysis

APM3201

Mathematical Programming

1.9.2.5.1.6.2

Multivariate Calculus, Linear Algebra I Multivariate Calculus, Linear Algebra I APM2101, APM2201 Multivariate Calculus, Linear Algebra I Multivariate Calculus, Linear Algebra I APM2101, APM2201

Real Analysis I, Real Analysis I,

Real Analysis I, Real Analysis I,

Award of Qualification

The qualification will be awarded after the satisfaction of the programme requirements, including completion of 360 credits with a minimum of 120 credits obtained at each level. See also Rule G12 of the General Prospectus. 1.9.2.5.1.6.3

Programme Tuition Fees

Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition fees, application fees, registration fees, late registration-fees and other student fees. 1.9.2.5.1.6.4

Articulation

Vertical Vertical Articulation is possible with: BSc Hons Mathematics and BSc Hons Applied Mathematics, NQF Level 8 Horizontal Within WSU Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc Applied Statistical Science. Other Universities Horizontal Articulation is possible with NQF Level 7 qualifications offered by other institutions, subject to the relevant institution’s admission requirements. 1.9.2.5.1.6.5

Core Syllabi of Courses Offered

MAT1101: Precalculus & Calculus I Module Code Module Name NQF Level Credits Semester MAT1101 5 16 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 1 x 100 min 13 160

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

32

Content / Syllabus Sets, definitions, examples, operations on sets, complementation and DeMorgan’s laws. The real number system, graphs of linear, quadratic, polynomial and rational functions, exponential and logarithmic functions, trigonometric functions, inequalities. Linear systems. Limits, continuity and differentiability of functions of a single variable, curve sketching, maxima and minima, mean value theorems, indeterminate forms. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT1201: Precalculus & Calculus II Module Code Module Name NQF Level Credits MAT1201 5 16 Lectures per week Pracs per week Tutorials per week Number of weeks 4 x 50 min 1 x 100 min 13

Semester 1 Notional hours 160

Content / Syllabus Mathematical induction, permutations and combinations, binomial theorem, complex numbers and polar coordinates. Introduction to integration, integration of simple functions, fundamental theorem of integral calculus. Further techniques of integration, introduction to series and sequences, power series and Taylor polynomials and Taylor’s theorem, introduction to differential equations (ordinary differential equations of first order). Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT2101: Multivariate Calculus Module Code Module Name NQF Level Credits Semester MAT2101 6 8 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 80 Content / Syllabus Functions of several variables, surfaces, continuity, partial derivatives, implicit functions, the chain rule, higher order derivatives, Taylor’s theorem, local extrema and saddle points, multiple integrals, line integrals, Green’s theorem, Jacobians, spherical and cylindrical coordinates. Assessment

Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%.

MAT2102: Real Analysis I Module Code Module Name NQF Level Credits Semester MAT2102 6 8 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 80 33

2014

PROSPECTUS

Content / Syllabus Real number system as a complete ordered field, real sequences, convergent sequences, monotone sequences and monotone convergence theorem, subsequences, Cauchy sequences and Cauchy’s general principle of convergence, infinite series and various tests of convergence, functions on closed intervals. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT2201: Ordinary Differential Equations Module Code Module Name NQF Level Credits Semester MAT2201 6 8 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 80 Content / Syllabus Second order linear differential equations with constant coefficients, non-homogeneous equations, special methods for particular integrals, variation of parameters, higher order differential equations, solution in series, applications. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT2202: Linear Algebra I Module Code

Module Name NQF Level

Credits

Semester

MAT2202 6 8 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 80 Content / Syllabus Further properties of matrices and determinants, real vector spaces, basis and dimension, linear transformations, eigenvalues, diagonalization. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT3101: Real Analysis II Module Code Module Name NQF Level Credits MAT3101 7 16 Lectures per week Pracs per week Tutorials per week Number of weeks 2 x 50 min 2 x 50 min 13

Semester 1 Notional hours 160

Content / Syllabus Countable and uncountable sets, topology of real line; open and closed sets of R and their properties, limit points and the Bolzano - Weirstrass Theorem for sets, subsequences and the Bolzano - Weierstrass Theorem, compact sets and the Heine-Borel Theorem, uniform continuity, Riemann integration, uniform convergence.

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

34

Assessment

Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%.

MAT3102: Linear Algebra II Module Code

Module Name

NQF Level

Credits

Semester

MAT3102 7 16 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 2 x 50 min 13 160 Content / Syllabus Inner product spaces, the Cauchy - Schwarz and triangle inequalities, orthogonality and orthonormal bases, the Gram -Schmidt orthogonalization process, complex inner product spaces. eigenvalues and eigenvectors, diagonalization of a matrix, real symmetric matrices, complex eigenvalues, quadratic forms. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT3201: Abstract Algebra Module Code Module Name NQF Level Credits Semester MAT3201 7 16 2 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 2 x 50 min 13 160 Content / Syllabus Group Theory; definition and examples, elementary properties, subgroups, cosets, Lagrange’s Theorem. Ring Theory; definitions, elementary properties, subrings and ideals, integral domains and fields, residue class rings, polynomial rings, congruences, prime and maximal ideals. Homomorphism Theorems; factor groups and rings, the Fundamental homomorphism theorem, embedding theorems. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT3202: Complex Analysis Module Code

Module Name

NQF Level

Credits

Semester

MAT3202 7 16 2 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 2 x 50 min 13 160 Content / Syllabus Functions of a complex variable, limit, continuity and differentiability, power series, integration, singularities and the calculus of residues, uniform convergence.

35

2014

PROSPECTUS

Assessment

Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%.

1.9.2.5.2

BSc Mathematics (Extended Programme): BSCME

The first 2 years of the BSc Mathematics (Extended Programme) are equivalent to the first year of the BSc Mathematics programme. In the last two years of the BSc Mathematics (Extended Programme) the students follow the BSc Mathematics programme from second year. At each of the years, 1, 2, 3 & 4, a student must accumulate at least 120 credits towards the total graduation credits. All the core modules (and foundation modules in the case of Level 1) must be taken at each Level. The remaining credits to satisfy the credit requirements at the respective level must be accumulated from the electives. The following table captures briefly the admission requirement and programme characteristics. See also Section 1.6 for Admission Requirements and Programme and Characteristics. 1.9.2.5.2.1



1.9.2.5.2.1.1

Curriculum Core and Foundation Modules

Level 1a (BSCME) Module Name Core Integrated Mathematics I Integrated Mathematics II Foundation Computer Science Fundamentals Academic Literacy I Introduction to Programming I Academic Literacy II Life Skills Level 1b (BSCME) Module Name Integrated Mathematics III Introduction to Linear & Vector Algebra Integrated Mathematics IV 1.9.2.5.2.1.2

Code

Credits

Semester

MAT1111 MAT1212

16 16

First Second

CSI1111 ACL1111 CSI1212 ACL1212 LSK1012

16 8 16 8 8

First First Second Second Second

Code MAT1113 APM1101 MAT1214

Credits 16 16 16

Semester First First Second

Electives

Level 1a (BSCME) Module Name Extended General Physics I Extended General Chemistry I SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

Code PHY1111 CHE1111 36

Credits 16 16

Semester First First

Extended General Physics II Extended Organic and Physical Chemistry I Level 1b (BSCME) Extended General Physics III Extended General Chemistry II Probability & Distribution theory I Extended General Physics IV Extended Organic and Physical Chemistry II Statistical Inference I 1.9.2.5.2.1.3 Code

PHY1212 CHE1212

16 16

Second Second

PHY1113 CHE1113 STA1101 PHY1214 CHE1214 STA1202

16 16 16 16 16 16

First First First Second Second Second

Pre-Requisite Courses

MAT1111 MAT1212 MAT1113 APM1101

Course Name Level I Integrated Mathematics I Integrated Mathematics II Integrated Mathematics III Linear Programming & Applied Computing

MAT1214 APM1201

Integrated Mathematics IV Introduction to Linear & Vector Algebra

1.9.2.5.2.2

Pre-Requisite Faculty admission requirements FACULTY admission requirements MAT1111 Introduction to Linear & Vector Algebra MAT1212 FACULTY admission requirements

Core Syllabi Of Courses Offered

MAT1111: Integrated Mathematics I Module Code Module Name NQF Level Credits MAT1111 5 16 Lectures per week Pracs per week Tutorials per week Number of weeks 2 x 50 min 1 x 100 min 13

Semester 1 Notional hours 160

Content / Syllabus Algebraic Expressions: Factorization; Remainder and Factor theorems; Nature of roots of a quadratic equation; Simplification of rational expressions; Radicals and Exponents; Change of subject of formula Sets: Definitions and Examples; Operations on sets; Venn Diagrams Real Numbers: The Real number system; Inequalities – linear, quadratic, rational and absolute value; Intervals on the Real line Functions: Definitions; Ways of representing a function (descriptive, algebraic, numerical and graphical); Polynomial, Rational, Absolute value, Exponential and Logarithmic functions; Symmetry; Even and Odd functions; Inverse of a function Limits and Continuity: Limit of a function; Standard limits; Limit theorems (without proof) and their applications; Continuous functions (A geometric and computational approach, minimizing the rigorous epsilon-delta approach)

37

2014

PROSPECTUS

Assessment

Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%.

MAT1212: Integrated Mathematics II Module Code Module Name NQF Level Credits Semester MAT1212 5 16 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 100 min 13 160 Content / Syllabus Differentiation, curve sketching, mean value theorems, applications of derivatives and partial differentiation Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT1113: Integrated Mathematics III Module Code Module Name NQF Level Credits Semester MAT1113 5 16 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 100 min 13 160 Content / Syllabus Intergration and its rules, areas, volumes and rotations of curves, Differential Equations (first order, first degree). Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT1214: Integrated Mathematics IV Module Code Module Name NQF Level Credits Semester MAT1214 5 16 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 100 min 13 160 Content / Syllabus Mathematical Induction: Principle of Mathematical Induction and its applications to standard proofs Sequences and Series: Arithmetic and Geometric sequences and series; Power series expansions; Taylor & Maclaurin series; Binomial series Complex Numbers: Cartesian and Polar co-ordinates and the conversion from one co-ordinate system to the other; Modulus and Argument; The Argand plane; De Moivre’s theorem; Euler’s formula Vectors: Basic concepts; Vector operations; The Dot product and the Cross product; Application to co-ordinate Matrices: Definitions and Examples; Algebra of matrices; The Inverse of a square matrix; The Determinant of a square matrix; Properties of Determinants

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

38

Assessment

Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%.

1.9.2.5.3

Honours BSc Mathematics: BSM

1.9.2.5.3.1

Entrepreneurship & Professional Development of Students

Mathematics is a scarce skill in South Africa and is crucial for the scientific and technological development that leads to economic development of the country. In view of this, the long term plan of the department envisages the establishment of a linkage between the department, industry and commerce. 1.9.2.5.3.2

Career Opportunities

A Bachelor of Science Honours degree in mathematics will prepare the student for jobs in statistical sciences, actuarial sciences, mathematical modeling, and cryptography; for teaching; as well as postgraduate training leading to a research career in mathematics. A strong background in mathematics is also necessary for research in many areas of computer science, social science, and engineering. 1.9.2.5.3.3

Purpose of Qualification

To provide basic mathematical knowledge needed for placement in jobs requiring a significant amount of mathematical maturity, and for further training at a higher level in various specializations of mathematics. 1.9.2.5.3.4

Exit Level Outcomes of The Programme

After the successful completion of the programme the student will be able to utilize the acquired skills in various disciplines such as Science and Engineering, Economic Sciences, Social Sciences and Humanities. 1.9.2.5.3.5

Programme Characteristics

1.9.2.5.3.5.1

Academic and Research Orientated

The programme is mainly academic and research orientated because academic study is research based and aimed at developing conceptual mathematical outcomes and training in new knowledge generation. 1.9.2.5.3.5.2

Practical Work

Research work provides the practical experience and the development of computing and research skills that will form the basis of future work, academic and research engagement. 1.9.2.5.3.5.3

Teaching and Learning Methodology

Learning activities include lecture, assignments, proposal development, hypothesising research 39

2014

PROSPECTUS

problems, data collection, capturing, analysis, interpretation, report writing, communications such as conference posters, papers. The programme is accredited with CHE and HEQC. 1.9.2.5.3.6

Programme Information

The entire programme is designed to consist of courses/modules in advanced Mathematics. 1.9.2.5.3.6.1

Minimum Admission Requirements

See Section 1.8 for Admission Requirements and Programme Rules. 1.9.2.5.3.6.2

Selection Criteria for New Students

All applicants will be interviewed for selection into the programme and immediately allocated supervisors for the research component of the course. 1.9.2.5.3.6.3

Curriculum

1.9.2.5.3.6.3.1 Required Modules The current Hons programme requires a selection of FOUR courses and a Compulsory Research Project as given below with the restriction that MAT 4101 cannot be taken concurrently either with MAT4105 or MAT4107. The total required credits are 126. Course Code

Course Name

Credits

Pre-Requisite

Algebra

MAT4101

24

Admission Requirements*

Classical Analysis

MAT4102

24

Admission Requirements

Functional Analysis

MAT4103

24

Admission Requirements

General Topology

MAT4104

24

Admission Requirements

Group Theory

MAT4105

24

Admission Requirements

Measure Theory

MAT4106

24

Admission Requirements

Ring Theory

MAT4107

24

Admission Requirements

Differential Equations MAT4108

24

Admission Requirements

Research Project (Compulsory)

30

MAT4109

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

40

1.9.2.5.3.6.3.2 Courses Offered Level 1 Module Name Algebra Classical Analysis Functional Analysis General Topology Group Theory Measure Theory Ring Theory Differential Equations Research Project (Compulsory)

Code MAT4101 MAT4102 MAT4103 MAT4104 MAT4105 MAT4106 MAT4107 MAT4108 MAT4109

Credits 24 24 24 24 24 24 24 24 30

Semester 1 and/or 2 1 and/or 2 1 and/or 2 1 and/or 2 1 and/or 2 1 and/or 2 1 and/or 2 1 and/or 2 1 and/or 2

1.9.2.5.3.6.3.3 Pre-Requisite Courses Course Code MAT4101 MAT4102 MAT4103 MAT4104 MAT4105 MAT4106 MAT4107 MAT4108 1.9.2.5.3.6.4

Course Name Algebra Classical Analysis Functional Analysis General Topology Group Theory Measure Theory Ring Theory Differential Equations

Pre-Requisite MAT3201 MAT3101 MAT3101 MAT3101 MAT3101, MAT3201 MAT3101 MAT3101, MAT3201 MAT2201

Award of Qualification

The qualification will be awarded after one completes 120 credits. [also see Rule G12 of the General Prospectus] 1.9.2.5.3.6.5

Programme Tuition Fees

Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition fees, application fees, registration fees, late registration-fees and other student fees. 1.9.2.5.3.6.6

Articulation

Vertical Vertical Articulation is possible with: MSc Mathematics, NQF Level 9 Horizontal Within WSU Horizontal Articulation is possible with NQF Level 8 qualifications offered by WSU, e.g. BSc Hons Applied Mathematics, NQF Level 8, subject to the admission requirements of that qualification. 41

2014

PROSPECTUS

Other Universities Horizontal Articulation is possible with NQF Level 8 qualifications offered by other institutions, subject to the relevant institution’s admission requirements. 1.9.2.5.3.6.7

Core Syllabi of Courses Offered

MAT4101: Algebra Module Code Module Name NQF Level Credits Semester MAT4101 8 24 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 1x 100 min 13 Content / Syllabus Ring theory; the isomorphism theorems, polynomial rings, the division algorithm, unique factorization domains, euclidean domain, theory of fields, Galois theory. Group theory; the isomorphism theorems, permutation groups, Sylow theorems, p-groups. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT4102: Classical Analysis Module Code MAT4102

Module Name NQF Level 8

Credits 24

Semester 1

Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 2 x 50 min 13 Content / Syllabus Study of the further properties of a function of a complex variable, conformal mappings, infinite products, analytic continuation, entire functions. Assessment

Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%.

MAT4103: Functional Analysis Module Code MAT4103

Module Name NQF Level Functional 8 Analysis

Credits 24

Semester 1

Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 2 x 50 min 13 Content / Syllabus A brief review of the theory of metric spaces, normed spaces and their completeness (Banach spaces), linear transformations, Hahn-Banach theorem, reflexivity, open mapping theorem, closed graph theorem and the principle of uniform boundedness, basic theory of Hilbert spaces and finite dimensional spectral theory. SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

42

Assessment

Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%.

MAT4104: General Topology Module Code MAT4104

Module Name NQF Level General 8 Topology

Lectures per week Pracs per week 4 x 50 min

Credits 24

Semester 1

Tutorials per week Number of weeks Notional hours 2 x 50 min 13

Content / Syllabus Topological spaces, metric topology, convergence of sequences and nets in topological spaces, continuity and homeomorphism, countability and separation, compactness, connectedness, product topology Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT4105: Group Theory Module Code MAT4105

Module Name Group Theory

NQF Level

Credits

Semester

8

24

1

Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 Content / Syllabus Isomorphism theorems, permutation groups, Cayley’s theorem, Sylow theorems, p-groups, classification of finite groups of low order, free groups, free abelian groups, fundamental theorem of abelian groups, group representations, the fundamental group in topology. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT4106: Measure Theory Module Code MAT4106

Module Name NQF Level Measure Theory 8

Lectures per week Pracs per week 4 x 50 min

Credits 24

Semester 1

Tutorials per week Number of weeks Notional hours 2 x 50 min 13

Content / Syllabus Measures; rings and algebras of sets, measures, outer measures, Borel measures on R, integration; measurable functions, product measures, the Lebesgue integral, decomposition and differentiation of measures; signed measures.

43

2014

PROSPECTUS

Assessment

Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%.

MAT4107: Ring Theory Module Code MAT4107

Module Name NQF Level Ring Theory 8

Credits 24

Semester 1

Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 2 x 50 min 13 Content / Syllabus Isomorphism theorems, embedding theorems, polynomial rings, the division algorithm, unique factorization domains, Euclidean domains, radical theory in commutative rings, theory of finite fields, Galois theory. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. MAT4108: Differential Equations Module Code MAT4108

Module Name NQF Level Differential 8 Equations

Credits 24

Semester 1

Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 2 x 50 min 13 Content / Syllabus Study of ordinary differential equations, including modeling physical systems, e.g. predator-prey population models; Analytic methods of solving ordinary differential equations of first and higher orders: Laplace Transform methods, series solutions, etc; Nonlinear autonomous systems: critical point analysis and phase plane diagrams; Numerical solution of differential equations; Introduction to partial differential equations. Assessment Semester mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester mark (DP) x 60% + Exam Mark x 40%. 1.9.2.5.4

MSc Mathematics

1.9.2.5.4.1

Entrepreneurship & Professional Development of Students

Mathematics is a scarce skill in South Africa and is crucial to the scientific and technological development that leads to economic development of the country. In view of this, the long term plan of the department envisages the establishment of a linkage between the department and industry and commerce.

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

44

1.9.2.5.4.2

Career Opportunities

A Master of Science degree in mathematics will prepare the student for jobs in statistics, actuarial sciences, mathematical modeling, and cryptography; for teaching; as well as postgraduate training leading to a research career in mathematics. A strong background in mathematics is also necessary for research in many areas of computer science, social science, and engineering 1.9.2.5.4.3

Purpose of Qualification

To provide mathematical knowledge needed for placement in jobs requiring a significant amount of mathematical maturity, and for further training at a higher level in various specializations of mathematics. 1.9.2.5.4.4

Exit Level Outcomes of The Programme

After the successful completion of the programme the student will be able to utilize the acquired skills in various disciplines such as Science and Engineering, Economic Sciences, Social Sciences and Humanities. 1.9.2.5.4.5

Programme Characteristics

1.9.2.5.4.5.1

Academic and Research Orientated

The programme is mainly academic and research orientated because academic study is research based and aimed at developing conceptual mathematical outcomes and training in new knowledge generation. 1.9.2.5.4.5.2

Practical Work

Research work provides the practical experience and the development of computing and research skills that will form the basis of future work, academic and research engagement. 1.9.2.5.4.5.3

Teaching and Learning Methodology

Learning activities include proposal development, hypothesising research problems, data collection, capturing, analysis, interpretation, report writing, communications such as conference posters, papers. The programme is accredited with CHE and HEQC. 1.9.2.5.4.6

Programme Information

1.9.2.5.4.6.1

Minimum Admission Requirements

A BSc Honours degree in Mathematics or Applied Mathematics. The department may put additional requirements. 1.9.2.5.4.6.2

Selection Criteria for New Students

All applicants will be interviewed for selection into the programme and immediately allocated 45

2014

PROSPECTUS

supervisors. 1.9.2.5.4.6.1

Curriculum

Core and Foundation Modules Year Level 1 1 2 2

Semester 1 2 3 4

Course Code Approved Proposal Presentation of Proposal Dissertation Presentation of Research Findings at Conferences

Credits 24 24 144 48

Total Credits 1.9.2.5.4.6.2

240 Available Topics/areas of research

Some of the typical areas of current research in the department include Algebra, Functional Analysis, Linear Operators, Nonlinear Functional Analysis, topology and Differential Equations. 1.9.2.5.4.6.3

Award of Qualification

The minimum number of credits for an MSc is 240, which may be accumulated entirely from a dissertation or split between coursework and a dissertation. 1.9.2.5.4.6.4

Programme Tuition Fees

Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition fees, application fees, registration fees, late registration-fees and other student fees. 1.9.2.5.4.6.5 Articulation Vertical Vertical Articulation is possible with: PhD Mathematics, NQF Level 10 Horizontal Within WSU Horizontal Articulation is possible with NQF Level 9 qualifications offered by WSU. Other Universities Horizontal Articulation is possible with NQF Level 9 qualifications offered by other institutions, subject to the relevant institution’s admission requirements. 1.9.2.5.4.6.6 Service Modules offered by the Department Site: NMD Module Name

Code

Credits

Level

Semester

Faculty/Dept

Special Mathematics I

SPM1101

16

I

I

FBML

Special Mathematics I

SPM1201

16

I

II

FBML

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

46

Site: BC Module Name

Code

Credits

Level Semester (Semesters)

Faculty/Dept

Mathematics S2

MATH2/0

10

2

S2

Civil

Quantitative Techniques

QAT1A13

24

2

S2

Markt

Quantitative Techniques

QAT1A13

24

2

S2

Markt

Business Calculations

BUC1001

12

1

S1

NHC Acc

Mathematics S1 Ext

EMAT1/0

12

1

S1

Elec

Maths Lit

MATHS10

6

1

S1

Food & C

Mathematics S2

MATH2/0

12

2

S2

Elec

Business Calculations Group 1

BUC1001

12

1

S1

Acc

Mathematics S1 Ext

MAT11E0

12

1

S1

AC

Mathematics S2

MAT2113

12

2

S2

AC

Mathematics S1

MAT1113

12

1

S1

AC

Mathematics S1

MATH1/0

12

1

S1

Elec

Mathematics S3

MATH3/0

12

3

S3

Elec

Business Calculations Group 2

BUC1001

12

1

S1

B

Business Calculations Group 3

BUC1001

12

1

S1

C

Business Calculations Group 4

BUC1001

12

1

S1

Ext

Mathematics S1

MATH1/0

10

1

S1

Civil

Mathematics S1 Ext

EMAT1/0

10

1

S1

Civil

Mathematics S2 Ext

EMAT2/0

10

2

S2

Civil

Mathematics S4

MATH4/0

12

4

S4

Elec

Quantitative Techniques Group 1

QAT1B14

10

2

S2

Markt

Quantitative Techniques Group 2

QAT1B14

10

2

S2

Markt

Statistics Group 1

STA2002

12

2

S2

Acc

Statistics Group 2

BST2002

12

2

S2

Acc

Maths Lit

MATHS20

6

2

S2

F&C

47

2014

PROSPECTUS

Site: Ibika & Chisielhurst Module Name

Code

Credits

Level Semester (Semesters)

Faculty/Dept

Mathematics S1

MATH1/0

10

1

S1

Civil

Mathematics S2

MATH2/0

10

2

S2

Civil

Mathematics S1 Ext

EATH1/0

10

1

S1&S2

Civil

Mathematics S2 Ext

EAHT2/0

10

2

S1 &S2

Civil

Mathematics S1 Ext

EMAT1/0

12

1

S1& S2

Elec

Mathematics S1

MATH1/0

12

1

S1

Elec

Mathematics S2

MATH2/0

12

2

S2

Elec

Mathematics S3

MATH3/0

12

3

S3

Elec

Mathematics S1 Ext

EMAT0/0

12

1

S1&S2

Mech

Mathematics S2 Ext

EMAT2/0

10

2

S1&S2

Mech

Mathematics S1

MATH1/0

12

1

S1

Mech

Mathematics S2

MATH2/0

10

2

S2

Mech

3

S3

Mathematics S3

MATH3/0

10

Applied Statisics

APST2/0

30

IT

IT Electronics

ITEL2/0

15

IT

1.9.3



1.9.3.1

Mech

Department of Statistics Information about Department

The Department of Statistics is located on the Mthatha campus of the university, at the Nelson Mandela Drive site offers undergraduate and postgraduate degree programmes in statistics. In addition it also offers service courses to other departments and faculties. The details of the programmes are given below Department Programmes offered

Duration Full-time

Department of Statistics

4yrs

Duration Delivery PartSites time N/A NMD

3yrs 1yrs 2yrs

N/A 3yrs 4yrs

1.9.3.2

BSc Applied Statistical Science Science - ECP BSc Applied Statistical Science BSc Honors Applied Statistical Science MSc

NMD NMD NMD

Mission of the Department

The Department of Statistics strives to serve as a national key source of graduates well-trained in statistical techniques appropriate for social research in all its dimensions and to provide training programmes suitable for the skills needs of the computing knowledge industries. SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

48

1.9.3.3

Goals of the Department

There are four key components of the goals of the department: • To produce problem-solving professional statisticians in areas identified in the mission statement; • To foster the teaching of statistical methods across the diverse programmes of the Walter Sisulu University through service courses; • To promote statistical research in areas relating to national socio-economic development ; • To contribute significantly to the aims of South African Statistical Association (SASA) 1.9.3.4

Student Societies in the Department

Science Students Societies 1.9.3.5

Programmes In The Department

1.9.3.5.1

BSc Applied Statistical Science

1.9.3.5.1.1

Entrepeneurship & Professional Development of Students

Statistics is an important area of study and is needed in various sectors of government and industry and commerce. In view of this, the long term plan of the department envisages the establishment of a linkage between the department and industry and commerce. 1.9.3.5.1.2

Career Opportunities

A Bachelor of Science degree in Applied Statistical Science will prepare the student for jobs in many different sectors of the economy, including Agriculture, Banking, Economic Planning, Education, Engineering, Forestry, Health Research, Insurance, Manufacturing, Market Research, Monitoring & Evaluation, Scientific Research, Social Research, Transport. 1.9.3.5.1.3

Purpose of Qualification

To provide basic statistical knowledge in applied mathematics, computer science, mathematics and statistics with an inclination towards application in the solution of technical problems in the marketplace, and for further training at a higher level in various specializations needing a sound foundation in statistical Sciences. 1.9.3.5.1.4

Exit Level Outcomes of the Programme

A BSc Applied Statistics graduate should: • demonstrate knowledge and understanding of basic concepts and principles in applied statistics, • have a sound basis in applied statistics for further training in this area and/or other fields of study that require a foundation in applied statistics, • develop a culture of critical and analytical thinking and be able to apply scientific reasoning to societal issues, • demonstrate ability to apply statistics, • be able to manage and organize own learning activities responsibly, 49

2014

PROSPECTUS



be able to demonstrate ability to solve real-world problems requiring the application of techniques in statistics.

1.9.3.5.1.5

Programme Characteristics

1.9.3.5.1.5.1

Academic and Research Orientated Study

The programme is mainly academic and research orientated because academic study is combined with related practical work aimed at developing more conceptual mathematical than computational outcomes. The courses in this programme are developed co-operatively using inputs from internal and external academic sources on a continuous basis. 1.9.3.5.1.5.2

Practical Work

Practical work in tutorials and computer laboratories provides the practical experience and the development of computing and research skills that will form the basis of future work, academic and research engagement. 1.9.3.5.1.5.3

Teaching and Learning Methodology

Learning activities include lectures, tutorials, practicals in which in which independent study are integrated. 1.9.3.5.1.6

Programme Information

The entire programme must consist of credits from core modules in Statistics and related areas in the school. See also Section 1.5 for the Minimum Admission Requirements and Section 1.7 for Programme Rules. 1.9.3.5.1.6.1

Curriculum

A student must take all the Core modules and Foundational modules at that level. Relevant electives (for which the student has the required pre-requisites) must then be chosen so that the student has a minimum of 120 credits at that level. However, no student may register for more than 128 credits in any given academic year. 1.9.3.5.1.6.1.1 Core and Foundation Modules Level 1 Module Name Core Probability & Distribution Theory I Probability & Statistical Inference I Foundation Computer Literacy Communication Skills SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

50

Code

Credits

Semester

STA1101 STA1202

16 16

1 2

CLT1101 EDU1001

8 8

1 1

Total core credits Elective credits required Total credits Level 2 Module Name Probability & Distribution Theory II Statistical Inference II Total core credits Elective credits required Total credits Level 3 Module Name Sampling Theory & Methods Stochastic Processes & Time Series Forecasting Linear Model & Multivariable Distribution theory Total core credits Elective credits required Total credits

48 72 120 Code STA2101 STA2202

Credits 16 16 32 98 120

Semester First Second

Code STA3203 STA3202 STA3101

Credits 16 16 16 48 72 120

Semester Second Second First

Code

Credits

Semester

CHE1101 CSI1101 CSI1102 PHY1101 MAT1101 MAT1201 CHE1201 CSI1201 PHY1202 APM1101 APM1201

16 8 8 16 16 16 16 8 16 16 16

First First First First First Second Second Second Second First Second

Code APM2101 MAT2102 MAT2202 APM2201 APM2202 CHE2102

Credits 16 8 8 16 16 16

Semester First Second Second Second First First

1.9.3.5.1.6.1.2 Electives Level 1 Module Name General Chemistry I Information Systems and Applications Problem Solving and Programming General Physics I Precalculus & Calculus I Precalculus & Calculus II General Chemistry I Problem Solving and Programming General Physics II Introduction to Linear & Vector Alg. Linear Programming & Applied Computing Level 2 Module Name Numerical Analysis I Real Analysis I Linear Algebra I Eigenvalue Problems and Fourier Analysis Mechanics I Analytical Chemistry II 51

2014

PROSPECTUS

Physical Chemistry II Programming in JAVA Mechanics & Waves Multivariable Calculus Inorganic Chemistry II Organic Chemistry II Thermodynamics and Modern Physics Operating Systems Ordinary Differential Equations Minimum total credits Level 3 Module Name Numerical Methods Linear Algebra II Inorganic Chemistry III Organic Chemistry III Introduction to Artificial Intelligence Software Engineering I Electromagnetism and Quantum Mechanics Linear Models & Multivariable Distribution Theory Analytical Chemistry III Physical Chemistry III Environmental Chemistry – 2003 Data Management Software Engineering II Statistical Mechanics and Solid State Physics Complex Analysis Mathematical Programming

CHE2105 CSI2101 PHY2101 MAT2101 CHE2203 CHE2204 PHY2202 CSI2201 MAT2201

16 14 16 8 16 16 16 14 8 56

First First First First Second Second Second Second First

Code APM3101 MAT3102 HE3103 CHE3104 CSI3101 CSI3102 PHY3101 STA3101 CHE3202 CHE3205 CHE3207 CSI3201 (CSI3202 PHY3202 MAT3202 APM3201

Credits 16 16 16 8 14 14 24 16 16 16 12 14 14 24 16 16

Semester First First First First First First First First Second Second Second Second Second Second Second Second

1.9.3.5.1.6.1.3 Pre-Requisite Courses Module STA1101

Prerequisite

STA1202 STA2101

STA1101 STA1202 MAT1101 MAT1201 APM1101 APM1201

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

Concurrent MAT1101 APM1101 MAT1201 APM1201 MAT2101 MAT2102 APM2101

52

Substitutes

STA2201

STA3101

STA3202

1.9.3.5.1.6.2

STA1101 STA1202 MAT1101 MAT1201 APM1101 APM1201 STA2101 STA2202

MAT2201 MAT2202 APM2201

MAT3101 MAT3102 APM3101 MAT3201 MAT3202 APM3201

STA2101 STA2202 Award of Qualification

The qualification will be awarded after one satisfies the programme requirements, including completing 360 credits with a minimum of 120 credits obtained at each level. See also Rule G12 of the General Prospectus. 1.9.3.5.1.6.3

Programme Tuition Fees

Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition fees, application fees, registration fees, late registration-fees and other student fees. 1.9.3.5.1.6.4

Articulation

Vertical Vertical Articulation is possible with BSc Hons Mathematics and BSc Hons Applied Mathematics, NQF Level 8 Horizontal Within WSU Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc Applied Mathematics, NQF Level 7, course to the admission requirements of that qualification. Other Universities Horizontal Articulation is possible with NQF Level 7 qualifications offered by such institutions, subject to the relevant institution’s admission requirements. 1.9.3.5.1.6.5

Core Syllabi of Courses offered

NB. Course information on some of the modules offered outside the departments of statistics may be obtained from the respective departments. STA 1101: Probability & Distribution Theory 1 Module Code Module Name NQF Level Credits Semester STA1101 5 16 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 1 x 100 min 13 160 53

2014

PROSPECTUS

Content / Syllabus Data analysis and Descriptive Statistics Different kinds of variables and measurement scales. Construction and Graphical presentation of frequency distributions. Cumulative frequency; the ogive and percentiles. Measures of central tendency; the Mean, Median and Mode. Measures of Spread; Mean Deviation, the Standard Deviation and the Quartile Deviation. Probability Distributions Introduction to the concept of probability. Counting techniques, Baye’s theorem. Discrete probability distributions, including the Bernoulli, the Binomial, Poisson, Hyper-geometric, and Negative Binomial. Continuous Probability distributions including the Uniform, the Gamma, the Beta and the Chi-Square distributions, the Normal distribution. Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%. STA1202: Statistical Inference I Module Code Module Name NQF Level Credits Semester STA1202 5 16 2 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 1 x 100 min 13 160 Content / Syllabus Inferential Statistics: The Central Limit Theorem. Introduction to Sampling distributions including the t-distribution, the Chi-Square distribution and the F-distribution. Estimation of parameters. One and Two sample tests of hypotheses for means. The F-test. Simple Correlation, Simple Linear Regression Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%. STA2101: Probability & Distribution Theory II Module Code Module Name NQF Level Credits Semester STA2101 6 16 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 1 x 100 min 13 160 Content / Syllabus Combinatorial analysis, axioms of probability, conditional probability and stochastic inde­pendence. Introduction to the concept of a random variable. More detailed treatment of discrete probability distribution, Introduction to mathematical expectation and moment generating functions, Jointly distributed random variables, independent random variables, marginal and conditional distributions. The bivariate normal distribution, Functions of random variables; sums of random variables, The central limit theorem. Chebychev‘s inequality, De-Moivre-Laplace theorem. Poisson approximation to the binomial distribution.

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

54

Assessment

Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

STA2202: Statistical Inference II Module Code Module Name NQF Level Credits Semester STA2202 6 16 2 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 1x 100 min 13 160 Content / Syllabus Estimation: Properties of good estimators. Unbiased estimators. Consistent estimators. Maximum like¬lihood, method of moments, and least squares estimators. Interval estimation; confidence intervals for means, difference between two means, proportions. Confidence intervals for variances and ratio of variances.

Assessment

Hypothesis testing: Testing a statistical hypothesis; the Neyman-Pearson Lemma, the power function of a statistical test. likelihood ratio tests. Applications of hypothesis testing; tests concerning means, difference between two means, variances, proportions, differences among k proportions. Analysis of contingency tables, correlation and regression analysis, including multiple linear regression and correlation. Introduction to time series forecasting Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

STA3101: Multivariable Distribution Theory & Linear Models Module Code Module Name NQF Level Credits Semester STA3101 7 16 2 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 1x 100 min 13 160 Content / Syllabus Multivariate Distribution Theory: Random Vector: p-dimensional case , Joint distribution and their applications: p-dimensional case; Marginal & Conditional distributions and their applications to probability calculations, Marginal and Product Moments; Mean Vector; Covariance Matrix; Dispersion Matrix; Expectation of Random Quadratic Form. Joint Moment Generating Function and its applications; The Multivariate Normal Distribution; Quadratic Forms in Normal Variates. Linear Models: Concepts related to linear models; point and interval estimation; hypothesis testing; violation of assumptions; applications of linear models. Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%. 55

2014

PROSPECTUS

STA3202: Time Series & Stochastic Processes Module Code Module Name NQF Level Credits Semester STA3202 7 16 2 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 4 x 50 min 1x 100 min 13 160 Content / Syllabus Stochastic Processes: Introduction to stochastic processes. Finite markov chains with special emphasis on two state markov chains. Classification of states. The basic limit theorem of markov chains. Simple markov processes. The Poisson process. Birth and death processes. Introduction to inference for markov chains and markov processes. Time series forecasting: Forecasting a time series with no trend, forecasting a time series with a linear trend, fore­casting a time series with a quadratic trend. Forecasting seasonal time series. The multipli­cative decomposition model, Winter’s method. Forecasting a time series with additive sea­sonal variation; the use of regression models. Application of forecasting techniques. Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%. 1.9.3.5.2



BSc Applied Statistical Science (Extended Programme)

The first 2 years of the BSc Statistical Science (Extended Programme) are equivalent to the first year of the BSc Statistical Science programme. In the last two years of the BSc Statistical Science (Extended Programme) the students follow the BSc Statistical Science programme from second year. See section 1.5.2.5.1 At each of the years, 1, 2, 3 & 4, a student must accumulate at least 120 credits towards the total graduation credits. All the core modules (and foundation modules in the case of Level 1) must be taken at each Level. The remaining credits to satisfy the credit requirements at the respective level must be accumulated from the electives. The following table captures briefly the admission requirement and programme characteristics. See also Section 1.6 for Admission Requirements and Programme and Characteristics. 1.9.3.5.2.1



1.9.3.5.2.1.1

Curriculum Core and Foundation Modules

Level 1a (BSCEAS) Module Name Core Integrated Statistics I Integrated Statistics II Integrated Mathematics I Integrated Mathematics II SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

56

Code

Credits

Semester

STA1111 STA1212 MAT1111 MAT1212

16 16 16 16

First Second First Second

Foundation Computer Science Fundamentals Academic Literacy I Life Skills I Introduction to Programming I Academic Literacy II Life Skills II Level 1b (BSCEAS) Module Name Core Integrated Statistics III Integrated Statistics IV Integrated Mathematics III Integrated Mathematics IV Foundation Introduction to Computer Architecture Introduction to Programming II 1.9.3.5.2.1.2

CSI1111 ACL1111 LSK1111 CSI1212 ACL1212 LSK1212

16 8 8 16 8 8

First First First Second Second Second

Code

Credits

Semester

STA1113 STA1214 MAT1113 MAT1214

16 16 16 16

First Second First Second

CSI1113 CSI1214

16 16

First Second

Electives

Level 1a (BSCEAS) – An elective cannot be taken, presently, at this year because of exceeding credits Module Name Code Credits Semester Extended General Physics I PHY1111 16 First Extended General Chemistry I CHE1111 16 First Extended General Physics II PHY1212 16 Second Extended Organic and Physical Chemistry I CHE1212 16 Second Level 1b (BSCEAS) Module Name Code Credits Semester Introduction to Linear & Vector Algebra APM1101 16 First Extended General Physics III PHY1113 16 First Extended General Chemistry II CHE1113 16 First Probability & Distribution theory I STA1101 16 First Linear Programming & Applied Computing APM1201 16 Second Extended General Physics IV PHY1214 16 Second Extended Organic and Physical Chemistry II CHE1214 16 Second Statistical Inference I STA1202 16 Second 1.9.3.5.2.1.3

Pre-Requisite Courses

Course Code STA1111 STA1212

Course Name Integrated Statistics I Integrated Statistics II

Pre-Requisite Faculty admission requirements Faculty admission requirements 57

2014

PROSPECTUS

STA1113 STA1214 MAT1111 MAT1212 MAT1113 MAT1214 1.9.3.5.2.2

Integrated Integrated Integrated Integrated Integrated Integrated

Statistics III Statistics IV Mathematics Mathematics Mathematics Mathematics

I II III IV

Faculty admission requirements FACULTY admission requirements MAT1111 MAT1212

Award of Qualification

The qualification will be awarded after satisfaction of the programme requirements, including completing 360 credits with a minimum of 120 credits obtained at each level. Also see Rule G12 of the General Prospectus. 1.9.3.5.2.3

Programme Tuition Fees

Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition fees, application fees, registration fees, late registration-fees and other student fees. 1.9.3.5.2.4

Articulation

Vertical Vertical Articulation is possible with BSc Hons Mathematics and BSc Hons Applied Mathematics, NQF Level 8 Horizontal Within WSU Horizontal Articulation is possible with NQF Level 7 qualifications offered by WSU, e.g. BSc Applied Mathematics, NQF Level 7, course to the admission requirements of that qualification. Other Universities Horizontal Articulation is possible with NQF Level 7 qualifications offered by such institutions, subject to the relevant institution’s admission requirements. 1.9.3.5.2.5

Core Syllabi of Courses Offered

STA1111: Integrated Statistics I Module Code Module Name NQF Level Credits Semester STA1111 5 16 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 100 min 13 160

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

58

Content / Syllabus Descriptive Statistics: Different kinds of variables and measurement scales; Tabular and graphic presentation of data. Construction of frequency tables and their graphic presentation; Relationship of histogram with frequency curve; Stem & leaf diagram; Commonly used fractiles: their meanings and properties, Descriptive measures of central tendency and their properties; Descriptive measures of variation/dispersion and their properties. Economic Statistics (Index Numbers): Characteristics of index numbers of prices; Types of index numbers of prices & Methods of their construction: simple aggregative , weighted aggregative; quantity index numbers; cost of living index numbers. Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%. STA1212: Integrated Statistics II Module Code

Module Name

NQF Level

Credits

Semester

STA1212 5 16 2 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 100 min 13 160 Content / Syllabus Point & Interval Estimation : Meaning of point estimate . Illustrations with commonly used point estimates for population mean , variance ,and proportion . Basic normal-theory interval estimation of these parameters (both one-sample & two-sample cases). Hypothesis Testing : Normaltheory one-and two-sample-based tests of hypotheses about population means , variances & proportions. The chi-square test for independence . Simple Regression : Elementary treatment of the simple linear model. Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%. STA1113: Integrated Statistics III Module Code

Module Name

NQF Level

Credits

Semester

STA1113 5 16 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 100 min 13 160 Content / Syllabus Set Theory: Definition and examples of a set; Common set operations using Venn diagram; Basic laws of set algebra. Counting Techniques: Product rule for counting; concept of permutation and associated rules; concept of combination and associated rules. Probability I: Definition of probability. Basic rules for probability. Distributions I: Discrete probability distributions in general . The simple treatment of properties and probably calculations involving discrete uniform distribution , the Bernoulli, binomial, negative binomial Hypergeometric & Poisson distributions. Continuous distributions in general . The simple treatment of properties and probability calculations involving continuous uniform distribution , the nor­mal and the associated sampling distributions . 59

2014

PROSPECTUS

Assessment

Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%.

STA1214: Integrated Statistics IV Module Code Module Name STA1214 Lectures per week Pracs per week 2 x 50 min

NQF Level Credits Semester 5 16 2 Tutorials per week Number of weeks Notional hours 1 x 100 min 13 160

Content / Syllabus Point & Interval Estimation of parameters in general. One - and - two sample tests of hypotheses about population means, variances , & proportions. Correlation and regression. Significance tests in correlation. Linear regression point prediction. Curvillinear regression, significance tests in simple linear regression. Introduction to non-parametric tests. The sign test, Wilcoxon’s paired-sample test, Mann­Whitney U-test Assessment Semester Mark (DP) will be obtained assessments based on assignments and tests. Final mark will be obtained from the Semester Mark (DP) x 60% + Exam Mark x 40%. 1.9.2.5.3

BSc Honours (Statistical Science)

1.9.3.5.3.1

Entrepreneurship & Professional Development of Students

Statistics is a scarce skill in South Africa and is crucial to the scientific and technological development that leads to economic development of the country. In view of this, the long term plan of the department envisages the establishment of a linkage between the department and industry and commerce. 1.9.3.5.3.2

Career Opportunities

A Bachelor of Science degree in Applied Statistical Science will prepare the student for jobs in many different sectors of the economy, including Agriculture, Banking, Economic Planning, Education, Engineering, Forestry, Health Research, Insurance, Manufacturing, Market Research, Monitoring & Evaluation, Scientific Research, Social Research, Transport. 1.9.3.5.3.3

Purpose of Qualification

To provide advanced knowledge in Applied Statistical Sciences and prepare students for placement in various types of sectors. See also Section 1.9.3.5.1.3 for BSc Applied Statistical Science. 1.9.3.5.3.4

Exit Level Outcomes of the Programme

After the successful completion of the programme the student will be able to utilize the acquired skills in various disciplines such as Science and Engineering, Economic Sciences, Social Sciences and Humanities. SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

60

1.9.3.5.3.5

Programme Characteristics

1.9.3.5.3.5.1

Academic and Research Orientated

The programme is mainly academic and research orientated because academic study is research based and aimed at developing conceptual statistical outcomes and training in new knowledge generation. 1.9.3.5.3.5.2

Practical Work

Research work provides the practical experience and the development of computing and research skills that will form the basis of future work, academic and research engagement. 1.9.3.5.3.5.3

Teaching and Learning Methodology

Learning activities include lectures, assignments, proposal development, hypothesising research problems, data collection, capturing, analysis, interpretation, report writing, communications such as conference posters, papers. The programme is accredited with CHE and HEQC. 1.9.3.5.3.6

Programme Information

The entire programme is designed to consist of courses/modules in advanced Statistics. 1.9.3.5.3.6.1

Minimum Admission Requirements

An overall minimum of 55% in BSc in Statistics or an equivalent area. See also Section 1.8 for Programme Rules. 1.9.3.5.3.6.2

Selection Criteria for New Students

All applicants will be interviewed for selection into the programme and immediately allocated supervisors for the research component of the course. 1.9.3.5.3.6.3

Curriculum

1.9.3.5.3.6.3.1 Core and Foundation Modules Level 1 Module Name Elective 1 Elective 2 Elective 3 Elective 4 Elective 5 Total credits

Code Code Code Code Code Code

61

Credits 24 24 24 24 24 120

Semester 1 and/or 2 1 and/or 2 1 and/or 2 1 and/or 2 1 and/or 2

2014

PROSPECTUS

1.9.3.5.3.6.3.2 Electives Level 1 Module Name Advanced Probability and distribution theory Advanced Parametric statistical inference Advanced sampling theory & methods Advanced design and analysis of experiments Advanced general linear model Advanced Analysis of contingency tables Advanced nonparametric statistical inference Advanced Multivariate distribution theory Advanced special topics: Time series analysis Honours project (compulsory)

Code STA 4001 STA4002 STA4003 STA4004 STA4005 STA4006 STA4007 STA4008 STA4009 STA4010

Credits 24 24 24 24 24 24 24 24 24 8

1.9.3.5.3.6.3.3 Pre-Requisite Courses & Available Electives See Section 1.9.3.5.3.6.3.1 and 1.9.3.5.3.6.3.2— Curriculum 1.9.3.5.3.6.4

Award of Qualification

The qualification will be awarded after one completes 120 credits. Also see Rule G12 of the General Prospectus. 1.9.3.5.3.6.6

Programme Tuition Fees

Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition fees, application fees, registration fees, late registration-fees and other student fees. 1.9.3.5.3.6.6 Articulation Vertical Vertical Articulation is possible with MSc Statistics, NQF Level 9 Horizontal Within WSU Horizontal Articulation may be possible with some NQF Level 8 qualifications offered by WSU. Other Universities Horizontal Articulation is possible with NQF Level 8 qualifications offered by other institutions, subject to the relevant institution’s admission requirements.

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1.9.3.5.3.6.7

Core Syllabi of Courses Offered

STA4001: Advanced Probability and distribution theory Module Code

Module Name NQF Level

Credits

Semester

STA4001 8 24 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 Content / Syllabus Probability axioms, probability of finite sample spaces, conditional probability, and Bayes’ theorem. Random variables; Transformation of random variables; Order statistics. Mo­ ments and moment generating functions, Special distributions, Modes of convergence; con­vergence in probability, almost sure convergence, The weak and the strong laws of large numbers, The central limit theorem, Sampling distributions. Assessment

Year Mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%.

STA4002: Advanced parametric statistical inference Module Code Module Name NQF Level Credits Semester STA4002 8 24 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 Content / Syllabus Tests of significance; Point estimation; minimum variance unbiased estimation least square estimation, maximum likelihood estimation, Interval estimation, Hypothesis testing; Neyman-Pearson theory. Generalised likelihood ratio test, Asymptotic theory, Bayesian methods. Assessment

Year Mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%.

STA4003: Advanced sampling theory and methods Module Code Module Name NQF Level Credits STA4003 8 24 Lectures per week Pracs per week Tutorials per week Number of weeks 2 x 50 min 1 x 50 min 13

Semester 1 Notional hours

Content / Syllabus Advanced treatment of the commonly used sampling procedures, Multi-stage and multi­phase sampling; Non-sampling errors, Sequential sampling; Sequential probability ratio test, Sampling inspection and quality control. Assessment

Year Mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%. 63

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PROSPECTUS

STA4004: Advanced design and analysis of experiments Module Code Module Name NQF Level Credits Semester STA4004 8 24 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 Content / Syllabus Confounding in factorial experiments, Fractional replication, Response surface designs, Incomplete block designs. Assessment

Year Mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%.

STA4005: Advanced general linear model Module Code Module Name NQF Level Credits Semester STA4005 8 24 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 Content / Syllabus Applications of the general linear model, The regression model, Applications of the regres­sion and design models, The components -ofvariance model. ­ Assessment

Year Mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%.

STA4006: Advanced Analysis of contingency tables Module Code Module Name NQF Level Credits STA4006 8 24 Lectures per week Pracs per week Tutorials per week Number of weeks 2 x 50 min 1 x 50 min 13

Semester 1 Notional hours

Content / Syllabus Contingency tables and the chi-square test, 2x2 tables, McNemar’s test, Combining infor­ mation from several tables, Measures of association for contingency tables; Multi-dimen­sional tables, Log-linear models for contingency tables. Assessment

Year Mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%.

STA4007: Advanced nonparametric statistical inference Module Code Module Name NQF Level Credits Semester STA4007 8 24 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

64

Content / Syllabus Introduction to order statistics; Goodness-of-fit tests; the chi-square test, the Kolmogorov ­Smirnov one sample test. The sign test, the signedrank test; Two-sample problem; Mann-Whitney U-test; Linear rank test statistics for the location and scale parameters. Assessment

Year Mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%.

STA4008: Advanced Multivariate distribution theory Module Code Module Name NQF Level Credits Semester STA4008 8 24 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 Content / Syllabus The multivariate normal distribution, The Wishart distribution, Hypothesis testing concern­ing mean vectors, Application of Hotelling’s T2 –statistics, Multivariate analysis of variance. Introduction to principal components, factors analysis, and discriminant analysis. Assessment

Year Mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%.

STA4009: Advanced special topics: Time series analysis Module Code Module Name NQF Level Credits Semester STA4009 8 24 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 Content / Syllabus Estimation in the domain; Estimating the autocovariance and the autocorrelation functions, Interpreting the correlogram Fourier transformation; Deterministic Sinusoidal perturbation, Fourier analysis, Simple Sinusoidal model, The Nyquist frequency, Periodogram analysis, Transforming the truncated autocovariance function, Hanning and Hamming techniques, Smoothing the periodogram, Fourier transform. Confidence intervals for the spectrum, A comparison of different estimation procedures, Analyzing a continuous time series, Bivariate processes, Cross-covariance and Cross-correlation function, State-space models and the Kalmanfilter; Steady models, linear growth models, Forecasting; Univariate and Multivariate forecasting procedures, Modeling seasonality using dummy variable regression. Assessment Year Mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%.

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STA4010: Honours project (compulsory) Module Code Module Name NQF Level Credits Semester STA4010 8 32 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 2 x 50 min 1 x 50 min 13 Content / Syllabus The topic for the Honours project must be chosen from one of the nine module topics listed above. The findings from the project must be submitted in a short dissertation which will be examined by its supervisor and at least one external assessor. Assessment

1.9.3.5.4

Year mark (DP) will be obtained from assessments based on assignments and tests. Final mark will be obtained from the Year Mark (DP) x 60% + Exam Mark x 40%. MSc (Applied Statistical Science)

Candidates will be examined either on two (2) papers set on approved subjects and a dissertation, or on a dissertation only. 1.9.3.5.4.1

Entrepreneurship & Professional Development of Students

Statistical Science is a scarce skill in South Africa and is crucial to the scientific and technological development that leads to economic development of the country. In view of this, the long term plan of the department envisages the establishment of a linkage between the department and industry and commerce. 1.9.3.5.4.2

Career Opportunities

A Master of Science degree in Statistical Science will prepare the student for jobs in statistics, actuarial sciences, mathematical modeling, and cryptography; for teaching; as well as postgraduate training leading to a research career in Statistical Science. A strong background in Statistical Science is also necessary for research in many areas of computer science, social science, and engineering 1.9.3.5.4.3

Purpose of Qualification

To provide Statistical Science knowledge needed for placement in jobs requiring a significant amount of statistical maturity, and for further training at a higher level in various specializations of Statistical Science. 1.9.3.5.4.4

Exit Level Outcomes of the Programme

After the successful completion of the programme the student will be able to utilize the acquired skills in various disciplines such as Science and Engineering, Economic Sciences, Social Sciences and Humanities. SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

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1.9.3.5.4.5

Programme Characteristics

1.9.3.5.4.5.1

Academic and Research Orientated

The programme is mainly academic and research orientated because academic study is research based and aimed at developing conceptual mathematical outcomes and training in new knowledge generation. 1.9.3.5.4.5.2

Practical Work

Research work provides the practical experience and the development of computing and research skills that will form the basis of future work, academic and research engagement. 1.9.3.5.4.5.3

Teaching and Learning Methodology

Learning activities include proposal development, hypothesising research problems, data collection, capturing, analysis, interpretation, report writing, communications such as conference posters, papers. The programme is accredited with CHE and HEQC. 1.9.3.5.4.6

Programme Information

1.9.3.5.4.6.1

Minimum Admission Requirements

A BSc Honours degree in Statistical Science. 1.9.3.5.4.6.2

Selection Criteria for New Students

All applicants will be interviewed for selection into the programme and immediately allocated supervisors. 1.9.3.5.4.6.1

Curriculum

Core and Foundation Modules Year Level 1 1 2 2

Semester 1 2 3 4

Course Approved Proposal Presentation of Proposal Dissertation Presentation of Research Findings at Conferences

Total Credits 1.9.3.5.4.6.2

Code CHE5108 CHE5208 CHE5308 CHE5408

Credits 24 24 144 48 240

Available Topics/areas of research

Typical areas of current research in the department include Tensor methods in statistics and Non-linear regression analysis of data.

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PROSPECTUS

1.9.3.5.4.6.3

Award of Qualification

The minimum number of credits for an MSc is 240, which may be accumulated entirely from a dissertation or split between coursework and a dissertation. 1.9.3.5.4.6.4

Programme Tuition Fees

Students are referred to the Walter Sisulu University institutional Fee Booklet for costs of tuition fees, application fees, registration fees, late registration-fees and other student fees. 1.9.3.5.4.6.5

Articulation

Vertical Vertical Articulation is possible with: PhD Mathematics, NQF Level 10 Horizontal Within WSU Horizontal Articulation is possible with NQF Level 9 qualifications offered by WSU. Other Universities Horizontal Articulation is possible with NQF Level 9 qualifications offered by other institutions, subject to the relevant institution’s admission requirements. 1.9.3.5.4.6.6 Service Modules offered by the Department Site: NMD Module Name

Code

Credits

Level Semester Faculty/Dept

Applied Statistics I

APS1101

16

I

1

FBML, FSET, EDUCATION

Applied Statistics II APS1201 16 I 2 Course descriptors - Electives from other schools

FBML, FSET, EDUCATION

General Chemistry (Analytical and Inorganic) Module Code CHE 1101 Contact hours

Module Name Lectures/Tutorials per week 5 (4 lectures + 1 tutorial)

NQF Level 7 Practicals per week 1(3 hours)

Credits Semester 16 1 Number of N o t i o n a l weeks hours 12 160

Content / Syllabus Theory: 1. Matter and measurements; Mole concept and stoichiometry; Reactions between ions in aqueous solutions; Atoms, Molecules and Ions; Atomic theory, Periodic properties of the elements; Basic concepts of chemical bonding, Shapes of molecules

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

68

Module Outcomes After engagement with the module content and processes, the students should be able to: articulate basic chemistry terms/concepts, perform calculations based on chemical relationships, comprehend and follow experimental procedure, carry out experiments in chemistry, interpret experimental results, define different chemical methods, be aware of safety procedures in handling hazardous materials. Learning and Teaching Session Number Hours Total Learning and Lectures & Tutorials (4L + 1T) 12 5 60 Teaching Practicals 12 3 36 breakdown Total 96 Assessment Assessment Sessions Number Hours Total breakdown Tests 2 2 4 Assignments 2 Practical reports 12 Examination 1 3 3 Supp-examination 1 3 3 Total 7 Projected self Self study Sessions Number Hours Total study time Private study 57 breakdown Grand Total 160 C o n t i n u o u s Assignments: 15% Tests: 60% Practical mark: 25% Assessment (CA) Continuous assessment (CA) : Overall assessment (OA) = 60 : 40. Examination Written examination (WA) : overall assessment (OA) = 40 : 60. General Chemistry (Physical and Organic) Module Code

Module Name

CHE 1201 Contact hours

Lectures/Tutorials per week 5 (4 lectures + 1 tutorial)

Content / Syllabus

Module Outcomes

N Q F Level 7 Practicals per week 1(3 hours)

Credits 16 Number weeks 12

Semester 1 of N o t i o n a l hours 160

Theory: First year organic chemistry course = 24 lectures. 1. Introduction : Scope of organic chemistry. 2. General Principles. 3. Hydrocarbons. 4. Organic halogen compounds 5. Alcohols. 6. Aldehydes and ketones. 7. Carboxylic acids and their derivatives. 8. Amines. First Year Physical Chemistry Course = 24 lectures. 1. Intermolecular Forces, Liquids & Solids 2. Chemical thermodynamics. 3. Chemical equilibrium. 4. Acid and base equilibria. 5. Electrochemistry. 6. Introduction to chemical kinetics. After engagement with the module content and processes, the students should be able to: articulate basic chemistry terms/concepts, perform calculations based on chemical relationships, comprehend and follow experimental procedure, carry out experiments in chemistry, interpret experimental results, define different chemical methods, be aware of safety procedures in handling hazardous materials 69

2014

PROSPECTUS

Learning and Teaching breakdown Assessment breakdown

Projected self study time breakdown

Continuous Assessment (CA) Examination

Learning and Teaching Session Number Hours Total Lectures & Tutorials (4L + 1T) 12 5 60 Practicals 12 3 36 Total 96 Assessment Sessions Number Hours Total Tests 2 2 4 Assignments 2 Practical reports 12 Examination 1 3 3 Supp-examination 1 3 3 Total 7 Self study Sessions Number Hours Total Private study (include 57 assignments and self study) Grand Total 160 Assignments: 15% Tests: 60% Practical mark: 25% Continuous assessment (CA) : Overall assessment (OA) = 60 : 40. Written examination (WA) : overall assessment (OA) = 40 : 60.

Analytical Chemistry II Module Code CHE 2102 Contact hours

Content / Syllabus

Module Name

NQF Level Credits Semester 7 16 1 Lectures/Tutorials Practicals per week Number of weeks N o t i o n a l per week hours 4 hours (at least 1 6 hours 12 160 hour tutorial) Tools of Analytical Chemistry: Introduction to Analytical Chemistry. Calculations used in Analytical Chemistry. Errors in Chemical Analysis. Random Errors in Chemical Analysis. Statistical Data Treatment and Evaluation. Sampling, Standardization and Calibration. Quality Assurance in Chemical Analysis Chemical Equilibria: Aqueous Solutions and Chemical Equilibria. Effects of Electrolytes on Chemical Equilibria. Solving Equilibrium Calculations for Complex Systems. Classical Methods of Analysis. Gravimetric Methods of Analysis. Titrimetric Methods of Analysis: Precipitation Titrimetry. Principles of Neutralization Titrations. Titration Curves for Complex Acid/ Base Systems. Applications of Neutralization Titrations. Complexation Reactions and Titrations. Electrochemical Methods of Analysis. Introduction to Electrochemistry. Applications of Standard Electrode Potentials. Applications of Oxidation / Reduction Titrations. Potentiometry

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

70

Module Outcomes

Learning and Teaching breakdown Assessment breakdown

Projected self study time breakdown Continuous Assessment (CA) Examination

After engagement with the module content and processes, the students should be able to: Draw a representative sample and prepare it for chemical analysis; apply appropriate statistical techniques to obtain useful chemical information from raw data; operate a chemical quality assurance programme; have a knowledge of sampling and the principles of gravimetry and titrimetry; demonstrate competence in the practical use of gravimetric and titrimetric techniques in carrying out analysis; have ability to perform the calculations required to obtain useful chemical information from given analytical data. Learning and Teaching Session Number Hours Total Lectures & Tutorials 12 4 48 *Practicals 6 6 36 Total 84 Assessment Sessions Number Hours Total Tests (All levels) 2 2 4 Assignments 2 Practical reports 6 Examination 1 3 3 Supp-examination 1 3 3 Grand Total 7 Self study Sessions Number Hours Total Private study 69* Grand Total 160 Assignments: 15% Tests: 60% Practical mark: 25% Continuous assessment (CA) : Overall assessment (OA) = 60 : 40. Written examination (WA) : overall assessment (OA) = 40 : 60.

Analytical Chemistry III Module Code CHE 3202 Contact hours

Module Name Analytical Chemistry III Lectures/Tutorials per week

NQF Level 7 Pracs per week

4 hours (at least 1 hour tutorial) 6 hours Content / Syllabus

Credits 16 Number of weeks 12

Semester 1 Notional hours 160

Electrochemical Methods of analysis. Coulometry. Voltammetry. Spectral Methods of Analysis. Introduction to spectrophotometry. Molecular spectroscopy, Molecular spectroscopy equipment, Atomic spectroscopy. Chemical Separation Methods, Solvent extraction, Chromatography theory, Gas chromatography, Liquid chromatography, Other Chromatographic Techniques, Supercritical fluid chromatography, Electrophoresis, Affinity chromatography, Field Flow Fractionation, Mass Spectrometry for chromatographers, Hyphenated (Ancillary) Methods, Multidimensional chromatography, Introduction to Thermal Methods of Analysis, Introduction to Radiochemical Methods of Analysis. 71

2014

PROSPECTUS

Module Outcomes Learning and Teaching breakdown

Learning and Teaching Session Number Hours Total Lectures & Tutorials 12 4 48 Practicals 12 6 36 Total 84 Assessment Assessment Sessions Number Hours Total breakdown Tests 2 2 4 Assignments 2 Practical reports 6 Examination 1 3 3 Supp-examination 1 3 3 Grand Total 7 Projected self study Self study Sessions Number Hours Total time breakdown Private study 59 Grand Total 160 Continuous Assignments: 15% Tests: 60% Practical mark: 25% Assessment (CA) Continuous assessment (CA) : Overall assessment (OA) = 60 : 40. Examination Written examination (WA) : overall assessment (OA) = 40 : 60. Inorganic Chemistry II Module Code CHE 2203 Contact hours

Module Name

NQF Level Inorganic Chemistry 7 Lectures/Tutorials per week Pracs per week 4 hours (at least 1 hour tutorial): 6 hours

Credits 16 Number weeks 12

Semester 1 of N o t i o n a l hours 160

Content / Syllabus Theory: 1. The chemical bond. 2. Descriptive chemistry of the P-block elements. 3.Coordination chemistry. 4. Inorganic rings, chains and cages Learning Learning and Teaching Session Number Hours Total and Lectures & Tutorials 12 4 48 Teaching Practicals 12 6 72 breakdown Total 120 Assessment Assessment Sessions Number Hours Total breakdown Tests (All levels) 2 2 4 Assignments 2 Practical reports 6 Examination 1 3 3 Supp-examination 1 3 3 Grand Total 7 Projected self Self study Sessions Number Hours Total study time Private study 33 breakdown Grand Total 160 SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

72

C o n t i n u o u s Assignments: 15% Tests: 60% Practical mark: 25% Assessment (CA) Continuous assessment (CA) : Overall assessment (OA) = 60 : 40. Examination Written examination (WA) : overall assessment (OA) = 40 : 60. Supplementary Inorganic Chemistry III Module Code

Module Name

NQF Level Inorganic Chemistry III 7 Lectures/Tutorials per week Pracs per week 4 hours (at least 1 hour tutorial): 6 hours

CHE 3103 Contact hours

Content Syllabus

Credits

Semester

16 Number weeks 12

1 of N o t i o n a l hours 160

/ Theory: 1. The chemistry of d-block elements. 2. Structure of Transition metal compounds. 3.The chemistry of f-block elements. 4.Introduction to organo-metallic chemistry. 5.Introduction to bio-inorganic chemistry

Learning and Teaching breakdown Assessment breakdown

Projected self study time breakdown

Learning and Teaching Session Number Hours Total Lectures & Tutorials 12 4 48 Practicals 12 6 72 Total 120 Assessment Sessions Number Hours Total Tests (All levels) 2 2 4 Assignments 2 Practical reports 6 Examination 1 3 3 Supp-examination 1 3 3 Grand Total 7 Self study Sessions Number Hours Total Private study 33 Grand Total 160 Assignments: 15% Tests: 60% Practical mark: 25% Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.

Continuous Assessment (CA) Examination Written examination (WA) : overall assessment (OA) = 40 : 60. Organic Chemistry II Module Code Module Name CHE 2204 Organic Chemistry Contact hours Lectures/Tutorials per week

NQF Level 7 Practicals per week 4 hours (at least 1 hour tutorial): 6 hours

73

Credits 16 Number of weeks 12

Semester 1 Notional hours 160

2014

PROSPECTUS

Content / Syllabus Learning and Teaching breakdown Assessment breakdown

Projected self study time breakdown Continuous Assessment (CA) Examination

Theory: 1.Basic Introduction and Revision 2. Stereo- and Alicyclic Chemistry 3. Nucleophilic substitution Reactions 4. Electrophilic substitution Reactions 5. Molecular Rearrangements, 6. Oxidation Reactions 7. Reduction Reactions 8. Spectroscopic Methods in Organic Synthesis Learning and Teaching Session Number Hours Total Lectures & Tutorials 12 4 48 Practicals 12 6 72 Total 120 Assessment Sessions Number Hours Total Tests (All levels) 2 2 4 Assignments 2 Practical reports 6 Examination 1 3 3 Supp-examination 1 3 3 Grand Total 7 Self study Sessions Number Hours Total Private study 33 Grand Total 160 Assignments: 15% Tests: 60% Practical mark: 25% Continuous assessment (CA) : Overall assessment (OA) = 60 : 40. Written examination (WA) : overall assessment (OA) = 40 : 60.

Organic Chemistry III Module Code Module Name

NQF Level CHE3104 Organic Chemistry III 7 Contact hours Lectures/Tutorials per week Pracs per week 6 hours (at least 1 hour tutorial) 6 hours Content Syllabus

Outcomes

Credits

Semester

16 Number weeks 12

1 of Notional hours 160

/ Theory: 1. Groups Protection in Organic Synthesis 2. Alkylation of Carbanions 3. Formation of C-C bonds by base-catalysed Condensations 4. Formation of C-C bonds by acid-catalysed Condensations 5. The Wittig Reaction 6. Cycloaddition Reactions (with emphasis on Diels-Alder Reaction) 7. Oxidations 9. Reductions 10. Further Aromatic Chemistry 11. Heterocyclic Chemistry 12. Basic Theory of NMR (both 1H and 13C NMR). After this course the student is expected to be able to: have deep understanding of organic chemistry in general and organic synthesis in particular, design a method for the preparation of a given compound, recognize named reactions, read and understand literature preparative protocols, interpret NMR spectra to find the structure and predict NMR spectra for a substance

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

74

Learning and Teaching breakdown Assessment breakdown

Projected self study time breakdown

Learning and Teaching Session Number Hours Total Lectures & Tutorials 12 4 48 Practicals 12 6 72 Total Year 120 Assessment Sessions Number Hours Total Tests 2 2 4 Assignments 2 Practical reports 6 Examination 1 3 3 Supp-examination 1 3 3 Grand Total 7 Self study Sessions Number Hours Total Private study 33 Grand Total 160 Assignments: 15% Tests: 60% Practical mark: 25% Continuous assessment (CA) : Overall assessment (OA) = 60 : 40.

Continuous Assessment (CA) Examination Written examination (WA) : overall assessment (OA) = 40 : 60. Physical Chemistry II Module Code CHE 2105 Contact hours

Module Name Physical Chemistry II Lectures/Tutorials per week 4 hours (+ at least 1 hour tutorial):

75

NQF Level 7 Practicals per week 6 hours

Credits 16 Number of weeks 12

Semester 1 Notional hours 160

2014

PROSPECTUS

Content / Syllabus

Learning and Teaching breakdown Assessment breakdown

Projected self study time breakdown Continuous Assessment (CA) Examination

Theory: 1.Introduction: units, mathematical review. 2. The First Law of Thermodynamics: Heat, Work, the First Law. 3. Applying the First Law: Heat Capacities, Isothermal and Adiabatic Changes, Reversible and Irreversible Processes. 4. Thermochemistry: Heats of Reaction, Temperature Dependence of Reaction Enthalpies, Heat and Physical Changes. 5. The Second and Third Law of Thermodynamics: Heat Engines, Carnot Cycle, Entropy, Entropy Calculations and Absolute Entropies, the Third Law. 6. Work, free Energy and Chemical Equilibrium: Maximum Work, Free Energy, Thermodynamic Relations and their Manipulations. 7. The Equilibrium Constants for Ideal Gas Reactions. 8. Equilibrium Constants for Real Gases: Real Gas Behaviour, Van Der Waals Equation, Fugacity, Equilibrium Constants. 9. Phase Equilibrium: Stability of Phases, the Phase Rule, One-Component Systems, Slopes on a Phase Diagram; the Clapeyron Equation. 10. Colligative Properties of Ideal Solutions: Solutions, Raoult’s Law: the Ideal Solution., Partial Molar Quantities, Mixing of Ideal Solutions, Dilute Solutions and Henry’s Law, Activities, Osmotic Pressure, Freezing Point Depression and Boiling Point Elevation. 11. Electrochemical Cells: Classification, EMF and Electrode Potentials, Half-Cells, the Nernst Equation, Thermodynamic Data from Cell EMF’s. 12. Chemical Kinetics: The Concept of Rate of Reaction, Empirical Order of Reaction: Zero, First and Second-Order Reactions, HalfLives,Determining the Order of Reaction. Learning and Teaching Session Number Hours Total Lectures & Tutorials 12 4 48 Practicals 12 6 72 Total 120 Assessment Sessions Number Hours Total Tests (All levels) 2 2 4 Assignments 2 Practical reports 6 Examination 1 3 3 Supp-examination 1 3 3 Grand Total 7 Self study Sessions Number Hours Total Private study 33 Grand Total 160 Assignments: 20% Tests: 40% Practical mark: 40% Continuous assessment (CA) : Overall assessment (OA) = 60 : 40. Written examination (WA) : overall assessment (OA) = 40 : 60.

Physical Chemistry III Module Code CHE 3205 Contact hours

Module Name Physical Chemistry III Lectures/Tutorials per week

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

76

NQF Level Credits Semester 7 16 1 Practicals per N u m b e r week of weeks Notional hours

4 hours (+ at least 1 hour tutorial): 6 hours 12 160 Content / Syllabus Theory: 1. Reaction Mechanisms: the Concept of a Mechanism, Opposing Reactions and Equilibrium Constants, Consecutive and Parallel Reactions, Rate–Determining Step and Steady- State Approaches, Complex Reactions. 2. Theoretical Approaches to Chemical Kinetics: Temperature Dependence of Reaction Rate, the Collision Theory, the Activated Complex Theory, Unimolecular Reactions and the Lindemann Theory. 3. Surface Work: Surface Tension and Surface Energy, Bubbles and Drops, the Kelvin Equation, Gibbs Formulation for Adsorption, the Langmuir Adsorption Isotherm. 4. Matter and Waves: Simple Harmonic Motion, Wave Motion, Standing Waves, Blackbody Radiation and the Nuclear Atom, the Photoelectric Effect, Spectroscopy and the Bohr Atom, the De Broglie Relation. 5. Quantum Mechanics: the Schrodinger Equation, Postulates of Quantum Mechanics, Operators, Solutions of Schrodinger Equation: the Free Particle, the Particle in a Ring of Constant Potential , the Particle in a Box, the Particle in a Box with One Finite Wall; Tunneling. 6. Rotations and Vibrations of Atoms and Molecules: the Harmonic Oscillator: the Nature of the Harmonic Oscillator Wavefunctions, the Thermodynamics of Harmonic Oscillator Wavefunctions, the Rigid Diatomic Rotor, the Thermodynamics of the rigid Rotor. Learning Learning and Teaching Session Number Hours Total and Lectures & Tutorials 12 4 48 Teaching Practicals 12 6 72 breakdown Total 120 Assessment Assessment Sessions Number Hours Total breakdown 2 2 Tests (All levels) 4 Assignments 2 Practical reports 6 Examination 1 3 3 Supp-examination 1 3 3 Grand Total 7 Projected self study Self study Sessions Number Hours Total time breakdown Private study 33 Grand Total 160 Continuous Assignments: 20% Tests: 40% Practical mark: 40% Assessment (CA) Continuous assessment (CA) : Overall assessment (OA) = 60 : 40. Examination Written examination (WA) : overall assessment (OA) = 40 : 60. Student must obtain a term mark of at least 40% and an exam mark of at least 40% to qualify for a supplementary

77

2014

PROSPECTUS

Extended General Physics I Code PHY1111 Lectures per week

Course Practicals per week

NQF Level 5 Tutorials per week 1 x 50 min

Credits 16 Number of weeks 15

Semester 1 Notional hrs

4 x 50 min 1 x 150 min 160 Content / Syllabus: Science – a way of knowing; Measurements in Physics; Kinematics; Dynamics; Kinetic Theory, Properties of Matter & Modern Physics Assessment: Continuous Assessment mark : To qualify for examinations, student must attain 40% continuous assessment mark (CAS 100% = 50% from major tests + 30% from practicals + 20% from tutorials, other assessments & assignments). The contribution of CAS mark to Semester mark is 60%. Examination Mark : Paper I Theory (60%) + Paper II Practical (40%) = 100%. To qualify for overall assessment of semester mark, the student must obtain a minimum examination mark of 40%. The contribution of examination mark to semester mark is 40%. Overall Semester mark : 60% CAS + 40% Exam mark. To qualify for module credit (16), student must obtain a minimum of 50% semester mark. Supplementary Examination : To qualify for this, a student must obtain a semester mark of 40% - 49% Entry Assumptions/Pre-requisites: NSC – qualified to progress to a diploma course - achievement rating of 3(40-49%) or better in 4 recognized content 20 credit subjects including Mathematics & Physical science. Rating 2 in English & Life Skills. Matriculation : Senior Certificate with a minimum of E(HG)/D(SG) in Mathematics & Physical Science. E(SG) in English. Other requirements : Minimum achievement of 3 in SATAP tests in English, Mathematics & Science. Co-requisite : MAT1111 Extended General Physics II Code PHY1212 Lectures per week

Course

NQF Level Credits Semester 5 16 2 Practicals per week Tutorials per week Number of weeks Notional hrs 1 x 150 min 1 x 50 min 15 160

4 x 50 min Content / Syllabus: Thermodynamics; Magnetism, Static & Current Electricity; Electromagnetism; Wave theory, Longitudinal Sound waves; Electromagnetic waves, Light & Optics

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

78

Assessment: Continuous Assessment mark : To qualify for examinations, student must attain 40% continuous assessment mark (CAS 100% = 50% from major tests + 30% from practicals + 20% from tutorials, other assessments & assignments). The contribution of CAS mark to Semester mark is 60%. Examination Mark : Paper I Theory (60%) + Paper II Practical (40%) = 100%. To qualify for overall assessment of semester mark, the student must obtain a minimum examination mark of 40%. The contribution of examination mark to semester mark is 40%. Overall Semester mark : 60% CAS + 40% Exam mark. To qualify for module credit (16), student must obtain a minimum of 50% semester mark. Supplementary Examination : To qualify for this, a student must obtain a semester mark of 40% - 49% Entry Assumptions/Pre-requisites: NSC – qualified to progress to a diploma course - achievement rating of 3(40-49%) or better in 4 recognized content 20 credit subjects including Mathematics & Physical science. Rating 2 in English & Life Skills. Matriculation : Senior Certificate with a minimum of E(HG)/D(SG) in Mathematics & Physical Science. E(SG) in English. Other requirements : Minimum achievement of 3 in SATAP tests in English, Mathematics & Science. Co-requisite : MAT1212 Extended General Physics III Code Course NQF Level Credits Semester PHY1113 5 16 1 Lectures per week Practicals per week Tutorials per week Number of weeks N o t i o n a l hrs 4 x 50 min 1 x 150 min 1 x 50 min 15 160 Content / Syllabus: Vectors; Motion in 2 or 3 dimensions; Newton’s Laws; Circular Motion; Energy transfer; Linear Momentum & collisions; Static Equilibrium & elasticity; Temperature & heat; Kinetic theory of Gases; Heat engines, entropy & second law of thermodynamics Assessment: Continuous Assessment mark : To qualify for examinations, student must attain 40% continuous assessment mark (CAS 100% = 50% from major tests + 30% from practicals + 20% from tutorials, other assessments & assignments). The contribution of CAS mark to Semester mark is 60%. Examination Mark : Paper I Theory (60%) + Paper II Practical (40%) = 100%. To qualify for overall assessment of semester mark, the student must obtain a minimum examination mark of 40%. The contribution of examination mark to semester mark is 40%. Overall Semester mark : 60% CAS + 40% Exam mark. To qualify for module credit (16), student must obtain a minimum of 50% semester mark. Supplementary Examination : To qualify for this, a student must obtain a semester mark of 40% - 49% 79

2014

PROSPECTUS

Entry Assumptions/Pre-requisites: A pass in PHY1111, PHY1212, MAT1111 & MAT1212 Co-requisite : MAT1113 Extended General Physics IV Code Course NQF Level Credits Semester PHY1214 5 16 2 Lectures per week Practicals per week Tutorials per week Number of weeks N o t i o n a l hrs 4 x 50 min 1 x 150 min 1 x 50 min 15 160 Content / Syllabus: Wave motion; Sound waves; Superposition & standing waves; Electric fields; Gauss’s law; Electric potential; Capacitance & Dielectrics; Direct current circuits; Magnetism Assessment: Continuous Assessment mark : To qualify for examinations, student must attain 40% continuous assessment mark (CAS 100% = 50% from major tests + 30% from practicals + 20% from tutorials, other assessments & assignments). The contribution of CAS mark to Semester mark is 60%. Examination Mark : Paper I Theory (60%) + Paper II Practical (40%) = 100%. To qualify for overall assessment of semester mark, the student must obtain a minimum examination mark of 40%. The contribution of examination mark to semester mark is 40%. Overall Semester mark : 60% CAS + 40% Exam mark. To qualify for module credit (16), student must obtain a minimum of 50% semester mark. Supplementary Examination : To qualify for this, a student must obtain a semester mark of 40% - 49% Entry Assumptions/Pre-requisites: A pass in PHY1111, PHY1212, MAT1111 & MAT1212 Co-requisite : MAT1214 General Physics I Code Course NQF Level Credits Semester PHY 1101 5 16 1 Lectures per week Practicals per week Tutorials per week Number of weeks Notional hrs 4 x 50 min 1 x 180 min 1 x 50 min 15 160 Content / Syllabus: Introduction to Mechanics: Rectilinear Motion; Vector Algebra and Calculus; Motion in two and Three Dimensions; Newton’s laws; Gravitational force and friction; Statics and Elasticity; Circular motion and other applications of Newton’s Laws; Work, energy and power; Potential energy and conservation of energy; Linear momentum and collisions; Rotation of a rigid object about a fixed axis; Rolling motion; angular momentum and torque; Oscillatory motion; Fluid mechanics. Heat and Thermodynamics: Temperature; Heat and the First Law of Thermodynamics; Kinetic Theory of Gases; Heat, Energy; Entropy and Second Law of Thermodynamics SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

80

Assessment: Continuous Assessment Mark: To qualify for an end of semester examination, a candidate must attain at least a 40% continuous Assessment mark (CASS 100% = 50% from Major Tests + 30% Practical Assessment + 20% from tutorials, minor tests and other Assignments). Examination Mark: End of Semester Examination: 100% (a candidate should obtain a minimum of 40%) Overall Semester Mark: Final Semester Mark: 0.6 Continuous Assessment Mark + 0.4 Examination Mark. Classification of Performance: Award of Module Credits: To qualify for the award of 16 credits, a candidate must obtain a minimum of 50% in the overall Semester Mark. Supplementary Examination: To qualify to sit for this, a candidate should have obtained a semester mark of 40%-49%. Entry Assumptions/Pre-requisites: To register for this course, a candidate should have passed NSC with a “B” designation or equivalent. In addition, a grade of at least 4 should have been obtained in Mathematics and Physical Science. General Physics II Code Course NQF Level Credits Semester PHY 1202 5 16 1 Lectures per week Practicals per week Tutorials per week Number of weeks N o t i o n a l hrs 4 x 50 min 1 x 180 min 1 x 50 min 15 160 Content / Syllabus: Mechanical Waves: Wave motion; Sound waves; Superposition and Standing waves Geometrical Optics: The nature of light and laws of Geometric Optics. Electromagnetism: Electrostatics; Electric Potential, Gauss’ s Law; Capacitance and Dielectrics, Current and Resistance, Direct Current Circuits; Magnetic Fields and Forces; Induced Fields and Forces. Assessment: Continuous Assessment Mark: To qualify for an end of semester examination, a candidate must attain at least a 40% continuous Assessment mark (CASS 100% = 50% from Major Tests + 30% Practical Assessment + 20% from tutorials, minor tests and other Assignments). Examination Mark: End of Semester Examination: 100% (a candidate should obtain a minimum of 40%) Overall Semester Mark: Final Semester Mark: 0.6 Continuous Assessment Mark + 0.4 Examination Mark. Classification of Performance: Award of Module Credits: To qualify for the award of 16 credits, a candidate must obtain a minimum of 50% in the overall Semester Mark. Supplementary Examination: To qualify to sit for this, a candidate should have obtained a semester mark of 40%-49%. Entry Assumptions/Pre-requisites: To register for this course, a candidate should have passed NSC with a “B” designation or equivalent. In addition, a grade of at least 4 should have been obtained in Mathematics and Physical Science.

81

2014

PROSPECTUS

Code Course NQF Level Credits Semester PHY2101 Mechanics & Waves 6 16 1 Lectures per week Practicals per week Tutorials per week Number of weeks N o t i o n a l hrs 4 x 50 min 1 x 180 min 2 x 40 min 15 160 Content / Syllabus: Vector fundamentals; Rectilinear motion of a particle; Position dependent forces; The Harmonic oscillator; The general motion of a particle in three dimensions; Central forces; Dynamics of systems of particles; Coupled oscillators; The wave equation. Assessment: Modules mark (M) will be obtained from continuous assessment based on quizzes, tutorials, lab reports, and tests. The final mark will be obtained from the Module mark (M) and Summative Assessment (E) in the ratio 3:2. Entry Assumptions/Pre-requisites: PHY1101, PHY1202, MAT1101, MAT1201 Co-requisites: MAT2101, MAT2201 Thermodynamics and Modern Physics Code

Course

NQF Level

Credits

Semester

PHY2202 Lectures per week

6 16 2 Practicals per week Tutorials per week Number of weeks N o t i o n a l hrs 1 x 180 min 2 x 40 min 15 160

4 x 50 min Content / Syllabus: Thermodynamics Temperature, reversible processes and work, The First Law of thermodynamics, The Second Law of Thermodynamics, Entropy, The thermodynamic Potentials and the Maxwell relations, General thermodynamics relations, Change of phase, Open systems and the Chemical Potential, The third law of Thermodynamics. Modern Physics Atoms and Kinetic Theory (Atomic Theory of Matter, Kinetic Theory, Specific Heat of gases, The Maxwell Distribution of Velocities and Brownian Motion). Elementary Particles (Discovery of the electron, quantization of electric charge, the photon, neutron, antiparticles and spin, discovery of X-rays). The Quantum Theory of Light (Blackbody Radiation, The RayleighJeans Theory, Planck’s Theory of Radiation, Einstein’s transition Probabilities, Amplification through Stimulated emission, the Ruby and Neon Lasers). The Particle Nature of Photons (The Photoelectric Effect, The Compton Effect, The Dual Nature of Photons, the Wave Packet, The Uncertainty Principle). The Quantum Theory of Atom (Models of Thomson and Rutherford, Classical Scattering Cross-section, Bohr’s Theory of Atomic Spectra, The Franck-Hertz Experiment, X-ray Spectra and the Bohr Theory). Nuclear Physics (Binding Energy, Radioactivity, Nuclear Reactions, Nuclear fusion and fission). Nuclear Physics (Space-time and dynamics, relativity of mass, length contraction and time dilation). Assessment: Modules mark (M) will be obtained from continuous assessment based on quizzes, tutorials, lab reports, and tests. The final mark will be obtained from the Module mark (M) and Summative Assessment (E) in the ratio 3:2. Entry Assumptions/Pre-requisites: PHY1101, PHY1202, MAT1101, MAT1201 Co-requisites: MAT2101, MAT2201 SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

82

Electromagnetism & Quantum Mechanics Code

Course

NQF Level

Credits

Semester

PHY3101 7 24 1 Lectures per week Laboratory Tutorials per week Number of weeks Notional hours sessions per week 4 x 50 min 2 x 180 min 2 x 50 min 15 240 Content / Syllabus: ELECTROMAGNETISM: Vector analysis: Gradient, divergence and curl, fundamental theorems of calculus, Laplacian, curvilinear coordinate systems: Cartesian, cylindrical and spherical Coulomb’s law and electric scalar charges, electric fields and scalar potentials of distributed electric scalar charges: direct integration and Gauss’ law, Poisson’s and Laplace’s equations, equipotential surfaces, electric conductors Biot-Savart law and magnetic sources, magnetic fields and vector potentials, magnetic forces, magnetic fields by direct integration and Ampere’s circuital law, Faraday’s law and induced emf Electric and magnetic dipole moments and polarizations, linear isotropic and homogeneous media, electric and magnetic fields due to polarized media, hysteresis, Maxwell’s equations, boundary conditions QUANTUM MECHANICS: Statistical interpretation of the double-slit interference experiment; Derivation of the Schrödinger equation for a force-free region; Separation of the Schrödinger equation; Conditions of good behaviour for wave functions; Simple barrier problems; One dimensional potential well of infinite height; Two and three-dimensional problems, degeneracy; Parity; Graphical nature of wave functions; Operators in Quantum Mechanics; The harmonic oscillator; The hydrogen atom; Heisenberg Uncertainty Principle. Assessment: Modules mark (M) will be obtained from continuous assessment based on quizzes, tutorials, lab reports, and tests. The final mark will be obtained from the Module mark (M) and Summative Assessment (E) in the ratio 3:2. Entry Assumptions/Pre-requisites: PHY2101, PHY2202, MAT2101, MAT2102, MAT2201, MAT2202 Co-requisites: None

83

2014

PROSPECTUS

Statistical Mechanics & Solid State Physics Code Course NQF Level Credits Semester PHY3202 7 24 2 Lectures per week L a b o r a t o r y Tutorials per week Number of weeks Notional hrs sessions per week 4 x 50 min 2 x 180 min 2 x 50 min 15 240 Content / Syllabus: STATISTICAL MECHANICS: Statistical equilibrium; The Maxwell-Boltzmann distribution law; Thermal equilibrium; Application to Ideal gas; Entropy and heat in terms of statistical probability; Heat capacity of ideal monatomic and an ideal polyatomic gas; The principle of equipartition of energy; The Einstein Solid; Fermi-Dirac distribution law; The electron gas; Application of Fermi-Dirac statistics to electrons in metals; Bose-Einstein distribution law; The photon gas; Heat capacities of vibrating molecules and of solid bodies. SOLID STATE PHYSICS: Crystals: binding, structure, defects and growing techniques. Lattices dynamics: quantized vibrations, phonons and density of states, specific heat capacity and Debye law. Free electron theory of metals: density of states, specific heat capacity, electrical conductivity and Hall effect, Pauli paramagnetism, thermionic emission. Comparison of metals, insulators, semimetals and semiconductors, band structure. Magnetic properties of materials: types of magnetism, susceptibility and permeability. Dielectrics: polarization, temperature and frequency dependence of permittivity, ferroelectric and piezoelectric materials. Semiconductors: holes and conduction electrons, intrinsic and extrinsic semiconductors, donors and acceptors, temperature dependency of electrical conductivity Assessment: Modules mark (M) will be obtained from continuous assessment based on quizzes, tutorials, seminar presentations, lab reports, and tests. The final mark will be obtained from the Module mark (M) and Summative Assessment (E) in the ratio 3:2. Entry Assumptions/Pre-requisites: PHY2101, PHY2202, MAT2101, MAT2102, MAT2201, MAT2202 Co-requisites: None Introduction to Object Oriented Programming Module Code CSI 1201 Lectures per week 1 x 2 hrs Content / Syllabus Learning and Teaching breakdown

Module Name NQF Level Credits Semester 5 8 2 Pracs per week Tutorials per week Number of weeks N o t i o n a l hours 1 x 3 hrs(x 2 1 x 1hrs (x 2 14 84 groups) groups) Theory: Classes, Objects and data abstraction, Inheritance, polymorphism, Pointers, virtual functions, templates, exception handling. Learning and Teaching Session Lectures Practicals Tutorials Grand Total

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

84

Number 14 14 14

Hours 2 3 1

Total 28 56 14 84

Assessment breakdown

Assessment Sessions Number Hours Total Major tests 2 2 4 Practical Assessment 12 1 12 Assignments 2 2 4 Tutorial assignments 12 1 12 Summative assessment Examination 1 3 3 Re-examination (optional) Special examination (optional) Oral examination (optional) Grand Total 35 Projected self study Self study Sessions Number Hours Total time breakdown Private study 28 1 28 Group work 28 .5 14 Pre-assessment revision 12 .2 2.4 Grand Total 44.4 Entry MATRICULATION: Qualified for bachelors. At least 3 in mathematics, 2 rules in English and 2 in life orientation. REQUIRED NSC SUBJECTS (Compulsory): Mathematics, English Recommended: IT, CAT OTHER (SATAP): 3 in mathematics, (Should have cleared CSI1111 & CSI1212) Assessment Continuous Assessment (CA) (Compulsory): Two Assignments(30%), and progression Two Tests (40%), 12 tutorial assessments(10%) and 12 Practical rules assessments(20%) Examination (Compulsory): One examination (EA). The contribution of the examination (EA) to the overall assessment (OA) is 40%. OA = 60%(CA) + 40%(EA). Re-examination (Not compulsory): To qualify for re-examination students must obtain an overall assessment of between 40 and 49%. Exclusion from NA module Introduction to Information Systems Module Code CSI 1101 Lectures per week 1 x 2 hrs

Module Name NQF Level Credits Semester 5 8 1 Pracs per week Tutorials per week Number of weeks Notional hours 0

2 x 2hrs (x 2 groups)

85

14

84

2014

PROSPECTUS

Content / Syllabus Theory: Fundamentals of IS, Data and Information; Importance of Information Systems; Computer Based Information Systems, Information System Requirements: Input, Process, Output, Information Systems as seen by the user, End-User Computing Applications; Office Automation; Distributed computing  Hardware Fundamentals, Software Fundamentals, User Interfaces, Command driven interfaces; Menu driven interfaces; Icon and pointer based interfaces, Operating Systems; Applications Software; Programming languages, Developing Information Systems, The classic systems development life cycle Business Information Systems, Transactions Processing, Management Information Systems, Decision Support Systems, Expert Systems Learning Learning and Teaching Session Number Hours Total and Lectures 14 2 28 Teaching Practicals 0 0 0 breakdown Tutorials 28 2 56 Grand Total 84 Assessment Assessment Sessions Number Hours Total breakdown Major tests 2 2 4 Practical Assessment Assignments 2 2 4 Tutorial assignments 12 1 12 Summative assessment Examination 1 3 3 Re-examination (optional) Special examination (optional) Oral examination (optional) Grand Total 23 Self study Sessions Number Hours Total Projected self study time Private study 28 1 28 breakdown Group work 28 .5 14 Pre-assessment revision 12 .2 2.4 Grand Total 44.4 Entry MATRICULATION: Qualified for bachelors. At least 3 in mathematics, 2 in rules English and 2 in life orientation. REQUIRED NSC SUBJECTS (Compulsory): Mathematics, English Recommended: IT, CAT OTHER (SATAP): 3 in mathematics, Continuous Assessment (CA) (Compulsory): Two Assignments(40%), Two Assessment Tests (40%), 12 tutorial assessments(20%) and progression rules Examination (Compulsory): One examination (EA). The contribution of the examination (EA) to the overall assessment (OA) is 40%. OA = 60%(CA) + 40%(EA). Re-examination (Not compulsory): To qualify for re-examination students must obtain an overall assessment of between 40 and 49%. SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

86

Exclusion from module

NA

Introduction to Information Systems Module Code Module Name CSI 1101 Lectures per week Pracs per week 1 x 2 hrs 0

NQF Level Credits Semester 5 8 1 Tutorials per week Number of weeks Notional hours 2 x 2hrs (x 2 14 84 groups) Content / Syllabus Theory: Fundamentals of IS, Data and Information; Importance of Information Systems; Computer Based Information Systems, Information System Requirements: Input, Process, Output, Information Systems as seen by the user, End-User Computing Applications; Office Automation; Distributed computing  Hardware Fundamentals, Software Fundamentals, User Interfaces, Command driven interfaces; Menu driven interfaces; Icon and pointer based interfaces, Operating Systems; Applications Software; Programming languages, Developing Information Systems, The classic systems development life cycle Business Information Systems, Transactions Processing, Management Information Systems, Decision Support Systems, Expert Systems Learning and Teaching breakdown Assessment breakdown

Projected self study time breakdown

Learning and Teaching Session Lectures Practicals Tutorials Grand Total Assessment Sessions Major tests Practical Assessment Assignments Tutorial assignments Summative assessment Examination Re-examination (optional) Special examination (optional) Oral examination (optional) Grand Total Self study Sessions Private study Group work Pre-assessment revision Grand Total

87

Number 14 0 28

Hours 2 0 2

Number 2

Hours 2

Total 28 0 56 84 Total 4

2 12

2 1

4 12

1

3

3

Number 28 28 12

Hours 1 .5 .2

23 Total 28 14 2.4 44.4

2014

PROSPECTUS

Entry rules

Assessment and progression rules

Exclusion from module

MATRICULATION: Qualified for bachelors. At least 3 in mathematics, 2 in English and 2 in life orientation. REQUIRED NSC SUBJECTS (Compulsory): Mathematics, English Recommended: IT, CAT OTHER (SATAP): 3 in mathematics, Continuous Assessment (CA) (Compulsory): Two Assignments(40%), Two Tests (40%), 12 tutorial assessments(20%) Examination (Compulsory): One examination (EA). The contribution of the examination (EA) to the overall assessment (OA) is 40%. OA = 60%(CA) + 40%(EA). Re-examination (Not compulsory): To qualify for re-examination students must obtain an overall assessment of between 40 and 49%. NA

Operating Systems Module Code Module Name NQF Level CSI 2201 6 Lectures per week Practicals per week Tutorials per week 1 x 2 hr 1 x 2 hr

Credits 14 Number of weeks 14

Semester 1 Notional hours 140

Content / Syllabus Theory: Overview of operating systems, functionalities and characteristics of OS. Hardware concepts related to OS, CPU states, I/O channels, memory hierarchy, microprogramming, The concept of a process, operations on processes, process states, concurrent processes, process control block, process context. Job and processor scheduling, scheduling algorithms, process hierarchies. Problems of concurrent processes, critical sections, mutual exclusion. Mutual exclusion, process co-operation, producer and consumer processes. Semaphores: definition, init, wait, signal operations. Critical sections Interprocess Communication (IPC), Message Passing, Direct and Indirect Deadlocks. Memory organization and management, storage allocation. Virtual memory concepts, paging and segmentation, address mapping. Virtual storage management, page replacement strategies. File organization: blocking and buffering, file descriptor, directory structure File and Directory structures, blocks and fragments, directory tree, UNIX file structure. Practicals: Consist of 14 tutorials chosen from each section of content covered. Learning Learning and Teaching Session Number Hours Total and Lectures 14 2 28 Teaching Practicals breakdown Tutorials 14 2 28 Grand Total 56

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

88

Assessment breakdown

Projected self study time breakdown

Entry rules

Assessment and progression rules

Exclusion from module

Assessment Sessions Number Hours Total Major tests 3 1 3 Class tests Assignments Tutorial assignments 3 6 18 Summative assessment Examination 1 3 3 Re-examination (optional) 1 3 3 Special examination (optional) Oral examination (optional) Grand Total 27 Self study Sessions Number Hours Total Private study 14 4 Group work Pre-assessment revision Grand Total 56 MATRICULATION: Entry Requirements for the Science Faculty. REQUIRED NSC SUBJECTS (Compulsory): Entry Requirements for the Science Faculty. RECOMMENDED NSC SUBJECTS (Not compulsory): OTHER (specify): Pre-requisites: CSI1101, CSI1102, CSI1201and CSI1202, MAT1101, CSI1102, CSI1203 and MAT1201 or APM1101, APM1201 Continuous Assessment (CA) (Compulsory): The contribution of CA to the overall assessment (OA) is 60%. Examination (Compulsory): One examination (EA). The contribution of the examination (EA) to the overall assessment (OA) is 40%. Re-examination (Not compulsory): Faculty rules apply, whereby the student progresses from a lower level to the next.

89

2014

PROSPECTUS

Introduction to Artificial Intelligence Module Code CSI3101 Lectures per week 3 x 50 min Contents/Syllabus

Entry Rules Assessment and progression rules

Module Name NQF Level Credits Semester 6 14 1 Pracs per week Tutorials per week Number of weeks Notional hours 1 x 3 hrs 1 x 50 min 14 140 Theory: Introduction to AI , Definitions , Early work-A Historical Overview , The Turing Test ,Intelligent Agents , The Idea of an Agent , Types of Agents , Types of Environments, Solving Problems by Search , Problem Solving agents , Formulating Problems , Searching for Solutions Search Strategies , Uninformed Search Strategies , Breadth First Search , Depth First Search , Uniform Cost Path Search , Informed Search Methods , Best-First –Search , Greedy Search , A* Search, Game Playing , The 8 Puzzle , The 8 Queens problem , Tic-Tac-Toe, First Order Predicate Logic , Representation , Reasoning and Logic , Propositional Logic , Syntax and Semantics , Using First Order Logic, Learning Methods, Neural Networks and Learning. Practicals: Consist of 5 labs based on what is covered during lectures. Applicant must have Passed all Second Year Modules, CSI2202, CSI2102 Continuous Assessment (CA) (Compulsory): Two class tests (CT), five assignments (AA), three tutorial assignments (TA), a practical assessment (PA), an examination (EA) and a re-examination (RA). Examination (Compulsory): One examination (EA). The contribution of the examination (EA) to the overall assessment (OA) is 40%. OA = 60%(CA) + 40%(EA). To qualify for course credit students must obtain an overall assessment of 50%. Re-examination (Not compulsory): To qualify for re-examination students must obtain an overall assessment of between 40 and 49%.

Software Engineering I Module Code Module Name CSI3102 Lectures per week Pracs per week 3 x 50 min 1 x 3 hrs

NQF Level Credits 6 14 Tutorials per week Number of weeks 1 x 50 min 14

Semester 1 Notional hours 140

Content / Syllabus Theory: Need for Software Engineering, Problems in software development, What is software engineering? software process: the waterfall model, prototyping approaches, evolutionary development models, project management: scheduling, cost estimation, requirements & design analysis: requirements engineering, analysis, definition, specification, requirements document, functional and non-functional requirements, requirements evolution, ssadm: data flow diagrams, entity relationship modelling (logical data models), modelling with uml: use-cases, class diagrams, state diagrams, software design: principles of design, designing for reusability, adaptability and maintainability, design quality software architecture, testing: test plans, testing methods, test strategies software maintenance and evolution.: software change and maintenance, software re-engineering, software configuration management. Practicals: Consist of 5 labs based on what is covered during lectures. SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

90

Entry rules

MATRICULATION: Faculty rules apply REQUIRED NSC SUBJECTS (Compulsory): RECOMMENDED NSC SUBJECTS (Not compulsory): OTHER (specify): Applicant must have Passed all Second Year Modules, CSI2202, CSI2102 Assessment Continuous Assessment (CA) (Compulsory): Two class tests (CT), five and progression assignments (AA), three tutorial assignments (TA), a practical assessment rules (PA), an examination (EA) and a re-examination (RA). Examination (Compulsory): One examination (EA). The contribution of the examination (EA) to the overall assessment (OA) is 40%. OA = 60%(CA) + 40%(EA). To qualify for course credit students must obtain an overall assessment of 50%. Re-examination (Not compulsory): To qualify for re-examination students must obtain an overall assessment of between 40 and 49%. Exclusion from A student will be excluded from the course after failing the module twice. module A student excluded from a course may be re-admitted after presenting a similar course from another university for credit. Database Management Systems Module Code CSI3201 Lectures per week

Module Name Pracs per week

NQF Level 7 Tutorials per week 1 x 50 min

Credits 14 Number of weeks

Semester 1 Notional hours

14

140

3 x 50 min

1 x 3 hrs

Content / Syllabus

Theory: File Systems and Databases, The Relational Database Model, Structured Query Language (SQL), Entity Relationship (ER) Modeling, Normalisation of Database Tables, Database Design, Transaction Management and Concurrency Control, Distributed Database Management System, Object-Oriented Databases, Database Administration, Database and The Internet. Practicals: Consist of 5 labs based on what is covered during lectures. Applicant must have Passed all Second Year Modules, CSI2202, CSI2102 Continuous Assessment (CA) (Compulsory): Two class tests (CT), five assignments (AA), three tutorial assignments (TA), a practical assessment (PA), an examination (EA) and a re-examination (RA). Examination (Compulsory): One examination (EA). The contribution of the examination (EA) to the overall assessment (OA) is 40%. OA = 60%(CA) + 40%(EA). To qualify for course credit students must obtain an overall assessment of 50%. Re-examination (Not compulsory): To qualify for re-examination students must obtain an overall assessment of between 40 and 49%.

Entry Rules Assessment and progression rules

91

2014

PROSPECTUS

Software Computing II Module Code Module Name NQF Level Credits Semester CSI3202 7 14 1 Lectures per week Pracs per week Tutorials per week Number of weeks Notional hours 3 x 50 min 1 x 3 hrs 1 x 50 min 14 140 Content / Syllabus Theory: Software Computing principles revisited, Downstream software Computing activities, Internet software Architectures and Technologies, N-Tier Architectures, CORBA, J2EE and .NET architectures, Web Services, Design Patterns, GOF design Patterns, Web Architecture Patterns, UML Object Diagrams, Challenges and Pitfalls of Software Design, Techniques for design, Design as decision making and evaluation of trade-offs, Examples taken from Object Oriented Design, Architecture – Driving forces, Various examples, Code Construction - UML to code, code to UML, Configuration Management –Source code control and management , Source code processing , Group work support, Versions and Variants, CVS, Quality Assurance -Defect costs, Reliability, Standards, Testing – Types of test, verification and validation, Black and White Box testing, Test analysis and generation, Metrics – Examples and uses, Process and Project metrics, Object orientation metrics. Practicals: Consist of 5 labs based on what is covered during lectures. Entry Rules Applicant must have Passed all Second Year Modules, CSI2202, CSI2102 Assessment Continuous Assessment (CA) (Compulsory): Two class tests (CT), and progression five assignments (AA), three tutorial assignments (TA), a practical rules assessment (PA), an examination (EA) and a re-examination (RA). Examination (Compulsory): One examination (EA). The contribution of the examination (EA) to the overall assessment (OA) is 40%. OA = 60%(CA) + 40%(EA). To qualify for course credit students must obtain an overall assessment of 50%. Re-examination (Not compulsory): To qualify for re-examination students must obtain an overall assessment of between 40 and 49%.

SCHOOL OF MATHEMATICAL AND COMPUTATIONAL SCIENCES

92