Science

Master of Science in Statistics

The Master of Science in Statistics is a postgraduate programme that prepares professionals for advanced practice in statistical theory, data analysis, and statistical applications. The programme provides specialised training in mathematical statistics, biostatistics, social statistics, medical statistics, statistical computing, and research methods.

Core areas include probability theory, statistical inference, linear models, design and analysis of surveys, Bayesian methods, stochastic processes, multivariate analysis, time series, research methods, and thesis. Students engage with both theoretical and practical work through coursework, computing sessions, and research.

The programme is offered by the University of Nairobi, Jomo Kenyatta University of Agriculture and Technology, Egerton University, Multimedia University of Kenya, and Masinde Muliro University of Science and Technology as public institutions. UoN offers four specialisations: Mathematical Statistics, Biostatistics, Social Statistics, and Medical Statistics. The programme is available in full-time and part-time modes over two years, combining coursework with research.

Students develop competencies in statistical theory, inference, modelling, computing, data analysis, and research. The programme includes coursework, examinations, computing projects, and a supervised research thesis, preparing graduates for statistical analysis, research, and advisory roles across multiple sectors.

JKUAT charges approximately KES 140,000 per year, UoN charges approximately KES 362,500 per year, and MMUST charges approximately KES 124,000 per year. No private university confirmed offering this exact programme. Entry requires at least an Upper Second Class Honours degree in Statistics, Mathematics, or a related field from a recognised institution.

Graduates pursue careers as statisticians, biostatisticians, data analysts, research analysts, quantitative analysts, and lecturers across government statistics offices, research institutions, financial institutions, health organisations, NGOs, and universities.

Skills Required

Statistical Theory and Inference
Probability Theory and Stochastic Processes
Linear Models and Regression Analysis
Bayesian Methods and Data Analysis
Statistical Computing with R and SPSS
Design and Analysis of Surveys
Multivariate Statistical Analysis
Time Series Analysis and Forecasting
Research Methods in Statistics
Academic Writing and Thesis Research

Key Subjects

Probability Theory and Statistical Inference
Linear Models and Regression Analysis
Design and Analysis of Surveys
Bayesian Methods and Data Analysis
Stochastic Processes
Multivariate Statistical Analysis
Time Series Analysis and Forecasting
Statistical Computing
Research Methods in Statistics
Thesis Research

Certifications

KNBS Professional Membership
ISI Professional Membership

Specializations

Mathematical Statistics

Focuses on mathematical statistics, covering mathematics, statistics, theory, probability, and managing mathematical statistics and theoretical inference.

Biostatistics

Examines biostatistics, covering biology, statistics, health, data, and managing biostatistics and health data analysis.

Social Statistics

Covers social statistics, covering social, statistics, demography, data, and managing social statistics and demographic analysis.

Medical Statistics

Focuses on medical statistics, covering medical, statistics, health, epidemiology, and managing medical statistics and epidemiological analysis.

Statistical Computing

Examines statistical computing, covering computing, statistics, software, algorithms, and managing statistical computing and data processing.

Applied Statistics

Covers applied statistics, covering applied, statistics, methods, analysis, and managing applied statistics and practical data analysis.

Duration: 2 years
Public, up to: Ksh 352,000
Private, up to: Ksh 350,000
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

Probability Theory and Statistical Inference
Linear Models and Regression Analysis
Design and Analysis of Surveys
Bayesian Methods and Data Analysis
Stochastic Processes
Multivariate Statistical Analysis
Time Series Analysis and Forecasting
Statistical Computing
Research Methods in Statistics
Thesis Research

Modules

12 in the programme

Probability Theory
Year 1Semester 13 creditsCore
Examines probability theory, covering probability, theory, statistics, distributions, and managing probability theory and distributions.
Statistical Inference
Year 1Semester 13 creditsCore
Covers statistical inference, covering inference, statistics, estimation, testing, and managing statistical inference and hypothesis testing.
Linear Models and Regression
Year 1Semester 13 creditsCore
Examines linear models, covering models, regression, linear, analysis, and managing linear models and regression analysis.
Design and Analysis of Surveys
Year 1Semester 13 creditsCore
Covers survey design, covering surveys, design, sampling, analysis, and managing survey design and analysis.
Statistical Computing
Year 1Semester 13 creditsCore
Examines statistical computing, covering computing, statistics, software, R, and managing statistical computing and data processing.
Bayesian Methods and Data Analysis
Year 1Semester 23 creditsCore
Covers Bayesian methods, covering Bayesian, statistics, inference, probability, and managing Bayesian methods and data analysis.
Stochastic Processes
Year 1Semester 23 creditsCore
Examines stochastic processes, covering stochastic, processes, probability, modelling, and managing stochastic processes and modelling.
Research Methods in Statistics
Year 1Semester 23 creditsCore
Covers research, methods, statistics, design, and conducting research in statistics, preparing students for their thesis.
Multivariate Statistical Analysis
Year 2Semester 13 creditsCore
Examines multivariate analysis, covering multivariate, statistics, analysis, methods, and managing multivariate statistical analysis.
Time Series Analysis and Forecasting
Year 2Semester 13 creditsCore
Covers time series analysis, covering time, series, analysis, forecasting, and managing time series analysis and forecasting.
Statistical Consulting and Communication
Year 2Semester 13 creditsCore
Examines statistical consulting, covering consulting, communication, statistics, reporting, and managing statistical consulting and communication.
Research Thesis
Year 2Semester 212 creditsCore
Original supervised research thesis on a statistics topic, demonstrating mastery of research methods and statistical knowledge, assessed through written submission and oral defence.

Specialisations

Mathematical Statistics
Focuses on mathematical statistics, covering mathematics, statistics, theory, probability, and managing mathematical statistics and theoretical inference.
Biostatistics
Examines biostatistics, covering biology, statistics, health, data, and managing biostatistics and health data analysis.
Social Statistics
Covers social statistics, covering social, statistics, demography, data, and managing social statistics and demographic analysis.
Medical Statistics
Focuses on medical statistics, covering medical, statistics, health, epidemiology, and managing medical statistics and epidemiological analysis.
Statistical Computing
Examines statistical computing, covering computing, statistics, software, algorithms, and managing statistical computing and data processing.
Applied Statistics
Covers applied statistics, covering applied, statistics, methods, analysis, and managing applied statistics and practical data analysis.

A day as a student

A typical day during the MSc in Statistics programme combines lectures, computing sessions, seminars, and independent study. Sessions cover probability theory, statistical inference, linear models, Bayesian methods, and stochastic processes. Probability theory sessions examine probability, theory, statistics, distributions, and managing probability theory and distributions. Statistical inference sessions cover inference, statistics, estimation, testing, and managing statistical inference and hypothesis testing. Linear models sessions cover models, regression, linear, analysis, and managing linear models and regression analysis. Bayesian methods sessions cover Bayesian, statistics, inference, probability, and managing Bayesian methods and data analysis. Stochastic processes sessions cover stochastic, processes, probability, modelling, and managing stochastic processes. Multivariate analysis sessions cover multivariate, statistics, analysis, methods, and managing multivariate statistical analysis. Time series sessions cover time, series, analysis, forecasting, and managing time series analysis and forecasting. Computing sessions provide practical experience in R, SPSS, and Stata for statistical analysis. Seminars provide opportunities for presenting research findings and discussing current developments in statistics. The programme culminates in a supervised research thesis on a statistics topic.

The trade offs

In its favour

Programme offered at multiple public universities with different fee options and specialisations.
Programme provides four specialisation options at UoN: Mathematical, Biostatistics, Social, and Medical Statistics.
Graduates are in high demand across government, research, finance, health, and NGO sectors.
Programme combines theoretical knowledge with practical computing skills using R, SPSS, and Stata.

Against it

UoN fee data is estimated from MSc Mathematics, not confirmed for Statistics specifically.
No private university confirmed offering this exact programme.
Significant fee difference between MMUST (KES 124,000/year) and UoN (KES 362,500/year).
Programme requires strong background in statistics or mathematics.

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

Public131k to 352k

131k at Masinde Muliro University of Science and Technology352k at University of Nairobi

Private150k to 350k

150k at Kabarak University350k at USIU-Africa

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 ~352K/yr mathematics.uonbi.ac.ke; MMUST 131K/yr. Private unverified.

HELB postgraduate loans are available for Kenyan students. Universities may offer scholarships for eligible students. ISI and international statistics organisations may offer scholarships and fellowships for statistics research and education.

Funding options

HELB Postgraduate Loan
University Scholarship
ISI Scholarship

Scholarships

3 recorded

HELB Postgraduate Loan
LoanKsh 200,000Kenyan
Kenyan students pursuing postgraduate studies at recognised universities.
University Scholarship
ScholarshipKsh 140,000Kenyan
Universities may offer scholarships for eligible postgraduate statistics students.
ISI Scholarship
ScholarshipKsh 200,000
ISI and international statistics organisations may offer scholarships for statistics research and education.

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 at least an Upper Second Class Honours degree with Mathematics or Statistics as a major. Lower Second Class may be considered with relevant work experience. 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, computing projects, seminar presentations, and class participation.
Written Examinations
Examination70% of the mark
Written examinations covering probability theory, statistical inference, linear models, Bayesian methods, and stochastic processes.
Computing Project
Project40% of the mark
Practical assessment through computing projects, demonstrating statistical computing, data analysis, and reporting skills.
Research Thesis
Research100% of the mark
Original supervised research thesis on a statistics topic, demonstrating mastery of research methods and statistical knowledge, assessed through written submission and oral defence.

Accreditation

The programme is accredited by the Commission for University Education (CUE). University of Nairobi, JKUAT, Egerton University, Multimedia University of Kenya, and Masinde Muliro University of Science and Technology (public) offer MSc in Statistics. The programme meets CUE standards for postgraduate training in statistics. Graduates may interact with KNBS for official statistics standards and ISI for international statistics standards. The programme aligns with ISI global statistics frameworks.

Accredited by

Commission for University Education (CUE)
Academic accreditationRequired
Programme accredited by CUE. University of Nairobi, JKUAT, Egerton University, Multimedia University of Kenya, and Masinde Muliro University of Science and Technology (public) offer MSc in Statistics. The programme meets CUE standards for postgraduate training in statistics. Graduates may interact with KNBS for official statistics standards and ISI for international statistics standards. The programme aligns with ISI global statistics frameworks.

Where it leads

The roles it opens, and what you leave with.

Where graduates go

6 roles

Statistician
High demandKsh 120,000 to Ksh 400,000
Conducts statistical analysis, covering statistics, data, analysis, and managing statistical analysis and interpretation.
Biostatistician
High demandKsh 130,000 to Ksh 450,000
Conducts biostatistical analysis, covering biostatistics, health, data, and managing biostatistics and health data analysis.
Data Analyst
High demandKsh 100,000 to Ksh 350,000
Conducts data analysis, covering data, analysis, statistics, and managing data analysis and reporting.
Research Analyst
High demandKsh 100,000 to Ksh 350,000
Conducts research analysis, covering research, analysis, data, statistics, and managing research analysis and reporting.
Quantitative Analyst
High demandKsh 150,000 to Ksh 500,000
Conducts quantitative analysis, covering quantitative, analysis, finance, statistics, and managing quantitative analysis and modelling.
Statistics Lecturer
Moderate demandKsh 100,000 to Ksh 400,000
Teaches statistics at university or college level, overseeing instruction, research, and academic supervision.

Graduate outcomes

Where these fields lead

8 careers

Tools you will learn

R Statistical Software
SoftwarePrimary
R for statistical computing and data analysis, covering computing, statistics, analysis, and managing statistical computing and data processing.
SPSS
Software
SPSS for statistical data analysis, covering statistics, data, analysis, and managing statistical data analysis.
Stata
Software
Stata for statistical analysis and data management, covering statistics, analysis, data, and managing statistical data analysis.
Python
Software
Python for data analysis and computing, covering computing, data, analysis, and managing data analysis and computing.

Industry links

Common misconceptions

Statistics is just about numbers and calculations.
Statistics covers theory, inference, modelling, computing, research methods, and data analysis beyond just numbers and calculations.
This programme is only for mathematicians.
Statistics is for professionals from economics, biology, health sciences, social sciences, and engineering backgrounds, not just mathematicians.
Statistics has limited career prospects in Kenya.
Statistics graduates are in high demand in government, research institutions, financial institutions, health organisations, and NGOs.
This programme is the same as data science.
Statistics focuses on statistical theory, inference, and methodology, while data science combines statistics with computing and machine learning.
Statistics is only about data analysis.
The programme covers probability theory, stochastic processes, Bayesian methods, survey design, and research methods alongside data analysis.
You need to be good at mathematics to study statistics.
While mathematical foundations are important, statistics emphasises applied analysis, interpretation, and communication of data.