Programme Details


Master of Science in Biostatistics

Duration : 2 Years Credits : 180

This programme equips students with advanced knowledge and understanding of statistical methods as applied in medical and public health research, and other fields. This is a 2-year programme that is offered through block-release.

Why study this programme?

  • The programme is jointly offered by the departments of mathematical sciences, computer science, and population studies at UNIMA and Department of Epidemiology at KUHeS.
  • Students in the programme benefit from international scholars the University of Nambibia, Witwatersrand, and South African Medical Research Council through visiting lectureships.
  • The programme is part of the Sub-Saharan africa Consortium of Advanced Biostatistics Training (SSACAB) which is a project within the Developing Excellence in Leadership and Biostatistics Training in Africa (DELTAS) with headquarters at University of Witwatersrand in South Africa.

Admission Requirements

Candidates must have strong Bachelor’s degree majored in Statistics or Mathematics and any other related disciplines from an accredited university. Selected candidates with deficiency in some Mathematics/Statistics modules will be asked to attend bridging courses prior to enrolment.

Program Structure

This four-semester Master's program is structured around a set of core modules, electives, and a dissertation. The core modules will be offered to all students and are designed to provide students with the necessary fundamental knowledge needed for their specialized modules. The electives offer students a wide choice of specializations in the study of Biostatistics. Additionally, where necessary, bridging modules will be offered for qualifying applicants who missed important undergraduate courses considered crucial for this program. These modules target computing, data management, and research skills relevant for a master's student. Students will be required to take a total of at least 180 credits (at least 120 from taught modules and 60 from the dissertation). It's important to note that one credit point represents the amount of learning achieved through a notional 10 hours of learning time

Core Modules
Code Name Year Credits
STA611 Probability and Distribution Theory 2 3
STA612 Generalised Linear Modelling 2 3
STA613 Experimental Designs 2 3
STA614 Statistical Inference 2 3
STA621 Time-to-Event Data Analysis 2 3
STA622 Correlated and Longitudinal Data Analysis 2 3
STA623 Bayesian Biostatistics 2 3
STA624 Principles of Epidemiology 2 3
Optional Courses
Code Name Year Credits
Non-parametric Methods 2 3
Programme Monitoring and Evaluation 2 3
Discrete Data Analysis 2 3
Multivariate Data Analysis 2 3
Statistics for Clinical Trials 2 3
Spatial Statistics 2 3