Science

Master of Science in Biostatistics

The Master of Science in Biostatistics is a postgraduate programme that prepares professionals for advanced practice in health statistics, epidemiological methods, and clinical trial design. The programme combines statistical theory with health and medical data analysis application.

Core areas include biostatistical methods, epidemiology, survival analysis, clinical trials, statistical computing, survey sampling, health data management, Bayesian statistics, research methods, and thesis. Students engage with both statistical theory and practical health data analysis through coursework and research.

The programme is offered by Moi University, Kenyatta University, University of Nairobi, Karatina University, and JKUAT. All are public universities offering the programme over two academic years through full-time and part-time modes of study.

Students develop competencies in biostatistical methods, epidemiological analysis, survival analysis, clinical trial design, statistical computing, health data management, and research methods. The programme includes coursework, examinations, and a research thesis or project.

KU charges approximately KES 326,400/year for related statistics programmes. UoN charges approximately KES 354,000/year for science-based master's programmes. Entry requires a Bachelor's degree with Second Class Honours Upper Division in statistics, mathematics, public health, biological sciences, or related fields from a recognised university.

Graduates pursue careers as biostatisticians, health statisticians, clinical trial statisticians, epidemiologists, data analysts, and lecturers in biostatistics across health ministries, research institutions, hospitals, pharmaceutical companies, and universities.

Skills Required

Biostatistical Methods and Health Data Analysis
Epidemiological Methods and Study Design
Survival Analysis and Time-to-Event Modelling
Clinical Trial Design and Analysis
Statistical Computing with R and SAS
Survey Sampling and Health Surveys
Health Data Management and Informatics
Bayesian Statistics and Probabilistic Modelling
Research Methods in Biostatistics
Academic Writing and Thesis Research

Key Subjects

Biostatistical Methods and Health Data Analysis
Epidemiological Methods and Study Design
Survival Analysis and Time-to-Event Modelling
Clinical Trial Design and Analysis
Statistical Computing with R and SAS
Survey Sampling and Health Surveys
Health Data Management and Informatics
Bayesian Statistics and Probabilistic Modelling
Research Methods in Biostatistics
Thesis Research

Certifications

KNBS Statistical Certification
International Biometric Society Certification

Specializations

Epidemiological Methods

Focuses on epidemiological methods, covering study design, disease surveillance, outbreak investigation, causal inference, and managing epidemiological statistics.

Clinical Trials

Examines clinical trials, covering trial design, randomisation, sample size, interim analysis, trial monitoring, and managing clinical trial statistics.

Survival Analysis

Covers survival analysis, covering Kaplan-Meier methods, Cox regression, parametric models, competing risks, and managing survival analysis.

Health Surveys

Focuses on health surveys, covering sampling design, survey methodology, health indicators, demographic surveys, and managing health survey statistics.

Bayesian Biostatistics

Examines Bayesian biostatistics, covering Bayesian inference, prior distributions, MCMC, hierarchical models, and managing Bayesian biostatistics.

Genetic Statistics

Covers genetic statistics, covering genetic epidemiology, GWAS, linkage analysis, population genetics, and managing genetic statistics.

Duration: 2 years
Public, up to: Ksh 388,000
Job market: High

The programme

What you study, how long it takes, and how it is delivered.

Practicalities

Study mode: Full-time, Part-time
Attachment: 0 months
Average class: 20 students
Award: Masters

What you study

10 subjects

Biostatistical Methods and Health Data Analysis
Epidemiological Methods and Study Design
Survival Analysis and Time-to-Event Modelling
Clinical Trial Design and Analysis
Statistical Computing with R and SAS
Survey Sampling and Health Surveys
Health Data Management and Informatics
Bayesian Statistics and Probabilistic Modelling
Research Methods in Biostatistics
Thesis Research

Modules

12 in the programme

Biostatistical Methods and Health Data Analysis
Year 1Semester 13 creditsCore
Examines probability distributions, estimation, hypothesis testing, confidence intervals, non-parametric methods, and managing biostatistical methods.
Epidemiological Methods and Study Design
Year 1Semester 13 creditsCore
Covers study design, cohort studies, case-control studies, cross-sectional studies, causal inference, and managing epidemiological methods.
Research Methods in Biostatistics
Year 1Semester 13 creditsCore
Covers research design, data collection, analysis, ethical issues, and conducting biostatistical research, preparing students for their thesis.
Survival Analysis and Time-to-Event Modelling
Year 1Semester 23 creditsCore
Examines Kaplan-Meier methods, Cox proportional hazards, parametric models, competing risks, recurrent events, and managing survival analysis.
Clinical Trial Design and Analysis
Year 1Semester 23 creditsCore
Covers trial design, randomisation, blinding, sample size calculation, interim analysis, adaptive designs, and managing clinical trial statistics.
Statistical Computing with R and SAS
Year 1Semester 23 creditsCore
Examines R programming, SAS, data manipulation, simulation, reproducible research, visualisation, and managing statistical computing.
Survey Sampling and Health Surveys
Year 1Semester 23 creditsCore
Covers sampling design, stratification, cluster sampling, weighting, health surveys, demographic surveys, and managing survey statistics.
Health Data Management and Informatics
Year 2Semester 13 creditsCore
Examines health informatics, data quality, privacy, electronic health records, disease coding, and managing health data.
Bayesian Statistics and Probabilistic Modelling
Year 2Semester 13 creditsCore
Covers Bayesian inference, prior distributions, posterior distributions, MCMC, hierarchical models, and managing Bayesian biostatistics.
Genetic Statistics and Epidemiology
Year 2Semester 13 creditsCore
Examines genetic epidemiology, GWAS, linkage analysis, population genetics, molecular epidemiology, and managing genetic statistics.
Spatial Statistics and Disease Mapping
Year 2Semester 13 creditsCore
Covers spatial statistics, disease mapping, geostatistics, spatial epidemiology, cluster detection, and managing spatial health statistics.
Research Thesis or Project
Year 2Semester 26 creditsCore
Original research thesis or project on a biostatistics topic, demonstrating mastery of research methods and biostatistical knowledge, assessed through written submission and oral defence.

Specialisations

Epidemiological Methods
Focuses on epidemiological methods, covering study design, disease surveillance, outbreak investigation, causal inference, and managing epidemiological statistics.
Clinical Trials
Examines clinical trials, covering trial design, randomisation, sample size, interim analysis, trial monitoring, and managing clinical trial statistics.
Survival Analysis
Covers survival analysis, covering Kaplan-Meier methods, Cox regression, parametric models, competing risks, and managing survival analysis.
Health Surveys
Focuses on health surveys, covering sampling design, survey methodology, health indicators, demographic surveys, and managing health survey statistics.
Bayesian Biostatistics
Examines Bayesian biostatistics, covering Bayesian inference, prior distributions, MCMC, hierarchical models, and managing Bayesian biostatistics.
Genetic Statistics
Covers genetic statistics, covering genetic epidemiology, GWAS, linkage analysis, population genetics, and managing genetic statistics.

A day as a student

A typical day during the MSc in Biostatistics programme combines lectures, computer laboratory sessions, practical workshops, seminars, and independent study. Sessions cover biostatistical methods, epidemiology, survival analysis, clinical trials, and statistical computing. Biostatistical methods sessions examine probability distributions, estimation, hypothesis testing, confidence intervals, non-parametric methods, and managing biostatistical methods. Epidemiological methods sessions cover study design, cohort studies, case-control studies, cross-sectional studies, causal inference, and managing epidemiological methods. Survival analysis sessions cover Kaplan-Meier methods, Cox proportional hazards, parametric models, competing risks, recurrent events, and managing survival analysis. Clinical trials sessions cover trial design, randomisation, blinding, sample size calculation, interim analysis, and managing clinical trial statistics. Statistical computing sessions cover R programming, SAS, data manipulation, simulation, reproducible research, and managing statistical computing. Survey sampling sessions cover sampling design, stratification, cluster sampling, weighting, health surveys, and managing survey statistics. Health data management sessions cover health informatics, data quality, privacy, electronic health records, and managing health data. Bayesian statistics sessions cover Bayesian inference, prior distributions, posterior distributions, MCMC, hierarchical models, and managing Bayesian biostatistics. Genetic statistics sessions cover genetic epidemiology, GWAS, linkage analysis, population genetics, and managing genetic statistics. Research methods sessions prepare students for their thesis, covering research design, data collection, and analysis. Computer laboratory sessions provide hands-on experience with R, SAS, data analysis, clinical trial simulation, and epidemiological modelling. Seminars and discussion groups provide opportunities for debating current issues in biostatistics. Guest lectures from experienced biostatisticians, epidemiologists, and health researchers provide practical insights. The programme culminates in a research thesis on a biostatistics topic.

The trade offs

In its favour

High demand for biostatistics professionals with growing health research, clinical trials, disease surveillance, and evidence-based health policy in Kenya.
Programme offered by five public universities (Moi, KU, UoN, Karatina, JKUAT), providing wide institutional choice.
KU offers competitive fees at approximately KES 326,400/year for related statistics programmes.
Programme combines statistics with health sciences, epidemiology, and computing, providing versatile interdisciplinary skills.

Against it

UoN fees are higher at approximately KES 354,000/year for science-based master's programmes.
No private university confirmed offering this programme, limiting options.
Programme requires statistics, mathematics, or health sciences background, which limits access for non-related graduates.
Rapidly evolving field requires continuous self-learning beyond the programme curriculum.

What it costs

Tuition at both ends of the market, and how to pay for it.

What it costs, and where

Against 243 science courses

Public148k to 388k

148k at Kenyatta University388k at University of Nairobi

Annual tuition in Kenyan shillings, rounded. The upright tick is the median for this field, so a bar sitting entirely to its right is an expensive programme by the standards of its own subject.

The fine print

UoN MSc Statistics ~388K/yr (mathematics.uonbi.ac.ke). KU ~148K/yr (ku.ac.ke). Private: unverified.

HELB postgraduate loans are available for Kenyan students. KU may offer postgraduate bursaries for eligible students. KEMRI and health research organisations may provide training support for biostatistics professionals. Some pharmaceutical companies may sponsor staff for postgraduate study.

Funding options

HELB Postgraduate Loan
KU Postgraduate Bursary
KEMRI Training Support

Scholarships

3 recorded

HELB Postgraduate Loan
LoanKsh 200,000Kenyan
Kenyan students pursuing postgraduate studies at recognised universities.
KU Postgraduate Bursary
ScholarshipKsh 100,000Kenyan
Kenyatta University offers postgraduate bursaries for eligible students.
KEMRI Training Support
GrantKsh 300,000Kenyan
KEMRI and partner organisations may provide training support for biostatistics and health research professionals.

Getting in

The grades, the alternatives, and who accredits the award.

What you need

KCSE mean grade: N/A (Postgraduate)
Alternative entry: Most universities require Upper Second Class Honours in statistics, mathematics, public health, or biological sciences. Lower Second Division holders with relevant experience or postgraduate diploma are considered. Medical, pharmacy, nursing, and public health graduates are also eligible at some universities. Contact respective universities for specific admission requirements.

How you are assessed

4 components

Coursework and Continuous Assessment
Coursework30% of the mark
Continuous assessment through coursework assignments, problem sets, computer laboratory reports, seminar presentations, and class participation.
Written Examinations
Examination40% of the mark
Written examinations covering biostatistical methods, epidemiology, survival analysis, clinical trials, and statistical computing.
Computer Laboratory and Project Assessment
Practical30% of the mark
Practical assessment through computer laboratory exercises, data analysis projects, clinical trial simulation, epidemiological modelling, and demonstrating biostatistical skills.
Research Thesis or Project
Research100% of the mark
Original research thesis or project on a biostatistics topic, demonstrating mastery of research methods and biostatistical knowledge, assessed through written submission and oral defence.

Accreditation

The programme is accredited by the Commission for University Education (CUE). Moi University, Kenyatta University, University of Nairobi, Karatina University, and JKUAT (all public) offer MSc in Biostatistics or related programmes. All programmes meet CUE standards for postgraduate training in biostatistics. Graduates are eligible for KNBS statistical certification and International Biometric Society certification.

Accredited by

Commission for University Education (CUE)
Academic accreditationRequired
Programme accredited by CUE. Moi University, Kenyatta University, University of Nairobi, Karatina University, and JKUAT (all public) offer MSc in Biostatistics or related programmes. All programmes meet CUE standards for postgraduate training in biostatistics. Graduates are eligible for KNBS statistical certification and International Biometric Society certification.

Where it leads

The roles it opens, and what you leave with.

Where graduates go

6 roles

Biostatistician
High demandKsh 140,000 to Ksh 600,000
Conducts biostatistical analysis, overseeing health data analysis, clinical trial statistics, epidemiological modelling, and managing biostatistical work.
Health Statistician
High demandKsh 130,000 to Ksh 550,000
Analyses health data, overseeing health indicators, disease surveillance, health surveys, and managing health statistics.
Clinical Trial Statistician
High demandKsh 150,000 to Ksh 650,000
Designs and analyses clinical trials, overseeing trial design, randomisation, interim analysis, and managing clinical trial statistics.
Epidemiologist
High demandKsh 130,000 to Ksh 550,000
Conducts epidemiological research, overseeing disease surveillance, outbreak investigation, study design, and managing epidemiological research.
Data Analyst
High demandKsh 130,000 to Ksh 550,000
Analyses health and research data, overseeing data cleaning, analysis, visualisation, reporting, and managing data analysis.
Biostatistics Lecturer
Moderate demandKsh 120,000 to Ksh 500,000
Teaches biostatistics at university or college level, overseeing instruction, research, laboratory supervision, and academic supervision.

Graduate outcomes

Where these fields lead

8 careers

Tools you will learn

R
SoftwarePrimary
R statistical software for biostatistical analysis, covering survival analysis, clinical trials, epidemiological modelling, and managing statistical computing.
SAS
Software
SAS for clinical trial analysis, covering clinical trials, regulatory statistics, FDA submissions, and managing clinical trial data.
Stata
Software
Stata for epidemiological analysis, covering epidemiological methods, survey analysis, survival analysis, and managing epidemiological data.
Python
Software
Python for data science, covering pandas, numpy, scipy, data manipulation, machine learning, and managing health data.

Industry links

Common misconceptions

Biostatistics is just about health data.
Biostatistics covers comprehensive statistical theory, epidemiological methods, clinical trial design, survival analysis, Bayesian methods, and genetic statistics beyond just health data.
This programme is only for those who want to work in hospitals.
Biostatistics skills are valuable for research institutions, pharmaceutical industry, public health, government, academia, and non-governmental organisations beyond just hospitals.
Biostatistics has limited career prospects in Kenya.
With growing health research, clinical trials, disease surveillance, and evidence-based health policy, demand for biostatistics professionals is high in Kenya.
Clinical trials are just about testing drugs.
Clinical trials cover comprehensive trial design, randomisation, interim analysis, safety monitoring, adaptive designs, and regulatory compliance.
Epidemiology is just about counting cases.
Epidemiology covers comprehensive study design, causal inference, disease surveillance, outbreak investigation, and analytical epidemiology.
Bayesian statistics is just a different way of calculating.
Bayesian statistics covers comprehensive probabilistic modelling, prior information, posterior inference, MCMC, and hierarchical modelling.