Code | Faculty | Department |
---|---|---|
10243172 | Faculty of Health Sciences | Department: Immunology |
Credits | Duration | NQF level |
---|---|---|
Minimum duration of study: 1 year | Total credits: 120 | NQF level: 08 |
The following requirements are set for completing the programme:
1. Relevant bachelor’s (or equivalent) degree with at least one applicable biological subject as a major
2. A weighted average of at least 60% at final-year level
The prerequisites for admission to the honours degree in certain fields of study are indicated in the syllabuses of the specific department.
Also consult General Academic Regulations G16-G29.
The degree is conferred with distinction on a student who has obtained of at least 75% (not rounded) in the examination of the core module GIM 700 (written, oral, practical, etc.).
University of Pretoria Programme Qualification Mix (PQM) verification project
The higher education sector has undergone an extensive alignment to the Higher Education Qualification Sub-Framework (HEQF) across all institutions in South Africa. In order to comply with the HEQSF, all institutions are legally required to participate in a national initiative led by regulatory bodies such as the Department of Higher Education and Training (DHET), the Council on Higher Education (CHE), and the South African Qualifications Authority (SAQA). The University of Pretoria is presently engaged in an ongoing effort to align its qualifications and programmes with the HEQSF criteria. Current and prospective students should take note that changes to UP qualification and programme names, may occur as a result of the HEQSF initiative. Students are advised to contact their faculties if they have any questions.
Minimum credits: 120
Module content:
The role of statistics and the data analysis process, collecting data sensibly, graphical methods for describing data, numerical methods for describing data, summarizing bivariate data, probability, random variables and probability distributions, sampling variability and sampling distributions, estimation using a single sample, hypothesis testing using a single sample, comparing two populations or treatments, the analysis of categorical data and goodness-of-fit tests, simple linear regression and correlation: inferential methods, multiple regression analysis, analysis of variance, nonparametric (distribution-free) statistical methods. This course is designed as a statistics building block for a non-statistics major postgraduate student at master's level.
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