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Technology

Bachelor of Science in Statistics and Computing

The Bachelor of Science in Statistics and Computing is a degree programme that combines statistical theory with computing skills to prepare graduates for data-driven careers. The programme is offered at Moi University and the University of Eldoret, preparing graduates for roles in data analysis, statistical modelling, computing and data science.

The curriculum covers probability theory, mathematical statistics, regression analysis, sampling methods, experimental design, programming, database systems, data structures, statistical computing, time series analysis, categorical data analysis, computing methods, research methods and data visualisation. Students develop competencies in statistical analysis, programming and data management.

Throughout the programme, students engage in lectures, computing laboratory sessions, statistical software practicals, field visits, industrial attachment and research projects. The practical approach ensures graduates can apply statistical methods using computational tools, analyse complex datasets and develop data-driven solutions.

The programme emphasises the growing importance of statistical computing in research, business and governance, preparing students to support evidence-based decision-making across sectors. Students learn about statistical inference, data mining, computational statistics and the application of programming languages to statistical problems.

Graduates are equipped to work in research institutions, government statistics offices, financial institutions, insurance companies, technology firms, non-governmental organisations and consulting firms. They play a critical role in data analysis, statistical modelling and computational problem-solving.

Career opportunities exist in the Kenya National Bureau of Statistics, research institutions, banks, insurance companies, technology firms, NGOs and consulting companies. Graduates work as statisticians, data analysts, statistical programmers, research analysts and data scientists across multiple sectors.

Duration
4 years
Public, up to
Ksh 281,350
Private, up to
Ksh 441,500
Job market
Moderate

The programme

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

Practicalities

Study mode
Full-time, Part-time
Attachment
3 months
Average class
25 students
Award
Bachelor

What you study

10 subjects
  • Probability Theory
  • Mathematical Statistics
  • Regression Analysis
  • Sampling Methods
  • Programming
  • Database Systems
  • Statistical Computing
  • Time Series Analysis
  • Categorical Data Analysis
  • Research Methods

Modules

8 in the programme
  • Probability Theory and Mathematical Statistics

    Year 1Semester 13 creditsCore

    Probability distributions, statistical inference and the mathematical foundations of statistics.

  • Introduction to Programming and Computing

    Year 1Semester 23 creditsCore

    Programming fundamentals, computer applications and computational problem-solving.

  • Regression Analysis and Sampling Methods

    Year 2Semester 13 creditsCore

    Regression Analysis and Sampling Methods: Linear and multiple regression, sampling techniques and survey methodology. Covers theoretical foundations, practical applications, and industry-relevant s...

  • Statistical Computing and Data Analysis

    Year 2Semester 13 creditsCore

    Computing methods for statistical analysis, data manipulation and visualisation using R and Python.

  • Database Systems and Data Structures

    Year 2Semester 23 creditsCore

    Database design, data structures and data management for statistical applications.

  • Time Series and Categorical Data Analysis

    Year 3Semester 13 creditsCore

    Time Series and Categorical Data Analysis: Time series modelling, forecasting methods and analysis of categorical data. Covers data modelling, query optimisation, storage structures, and informatio...

  • Experimental Design and Research Methods

    Year 3Semester 23 creditsCore

    Experimental Design and Research Methods: Design of experiments, research methodology and statistical report writing. Covers quantitative and qualitative approaches, data collection, analysis, and ...

  • Computing Methods and Project

    Year 3Semester 23 creditsCore

    Advanced computing methods for statistics and a research project applying statistical computing.

Specialisations

  • Statistical Computing

    Focus on computational methods for statistics, programming and algorithm development for data analysis.

  • Applied Statistics

    Specialisation in sampling methods, experimental design and statistical inference for real-world applications.

  • Data Science and Analytics

    Focus on data mining, machine learning and big data analytics techniques. This specialisation equips graduates with discipline-specific competencies for professional practice in Kenya and the East African region, with pathways to postgraduate study and professional certification.

  • Biostatistics

    Specialisation in statistical methods for health research, clinical trials and epidemiology. This specialisation equips graduates with discipline-specific competencies for professional practice in Kenya and the East African region, with pathways to postgraduate study and professional certification.

A day as a student

A typical day involves attending probability theory lectures, writing R scripts for statistical analysis in the computing laboratory, designing experiments for data collection, analysing datasets using Python, and presenting statistical findings to peers.

The trade offs

In its favour

  • Accredited by the Commission for University Education (CUE).
  • Graduates are eligible for HELB loans and government funding.

Against it

  • Limited programme specialisation options may be available.
  • Competitive job market requiring practical experience and networking.

What it costs

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

What it costs, and where

Against 191 technology courses
Public281k to 281k
281k at University of Nairobi281k at University of Nairobi
Private110k to 442k
110k at Mount Kenya University442k 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 Statistics 281,350 KUCCPS. USIU Data Sci 441,500/yr. MKU Stats 110,000 KUCCPS.

Government scholarships cover up to 53% of tuition for needy students. HELB provides loans up to Ksh 60,000. DAAD offers scholarships for STEM students.

Funding options

  • HELB Undergraduate Loan

    Loan

    Kenyan citizens enrolled in accredited undergraduate programmes

  • Government Scholarship (New Funding Model)

    Scholarship

    Needy students placed by KUCCPS in public universities

  • DAAD Scholarship

    Scholarship

    Undergraduate students in STEM fields

Scholarships

3 recorded
  • Higher Education Loans Board (HELB) Loan

    LoanKsh 60,000Kenyan

    Kenyan students admitted to recognised universities demonstrating financial need.

  • Higher Education Fund (HEF)

    Government fundingKenyan

    Kenyan students in public universities under the new funding model based on financial need assessment.

  • County Government Bursaries

    BursaryKenyan

    Kenyan students from respective counties demonstrating financial need.

Getting in

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

What you need

KCSE mean grade
C+ (Plus)
Alternative entry
KCSE C+ (Plus) OR A Level with two principal passes; OR a relevant Diploma from a recognised institution; OR any other qualification recognised by the university senate and CUE.

How you are assessed

2 components
  • Continuous Assessment Tests and Assignments

    Coursework30% of the mark

    Written tests, assignments, and practical exercises throughout the semester.

  • End of Semester Examinations

    Examination70% of the mark

    Written examinations covering all course content for the semester.

Accreditation

Accredited by the Commission for University Education (CUE). The programme is offered at Moi University and the University of Eldoret.

Accredited by

  • Commission for University Education (CUE)

    Academic accreditationRequired

    CUE is the statutory body responsible for the accreditation and quality assurance of university programmes in Kenya.

Where it leads

The roles it opens, and what you leave with.

Where graduates go

4 roles
  • Graduate Trainee

    High demandKsh 40,000 to Ksh 60,000

    Entry-level position applying academic knowledge in a professional environment.

  • Research Assistant

    Moderate demandKsh 45,000 to Ksh 65,000

    Supporting research projects through data collection, analysis, and reporting.

  • Project Officer

    High demandKsh 55,000 to Ksh 80,000

    Coordinating and implementing projects in public, private, or NGO sectors.

  • Analyst

    High demandKsh 60,000 to Ksh 90,000

    Analysing data, trends, and patterns to support decision-making.

Graduate outcomes

Graduates pursue careers as statisticians, data analysts, statistical programmers and research analysts in the Kenya National Bureau of Statistics, banks, insurance companies, technology firms and research institutions.

Where these fields lead

8 careers

Tools you will learn

  • R

    SoftwarePrimary

    Statistical computing language for data analysis, statistical modelling and visualisation.

  • Python

    SoftwarePrimary

    Programming language for data analysis, statistical computing and machine learning.

  • SPSS

    Software

    Statistical analysis software for survey data analysis and hypothesis testing.

  • SAS

    Software

    Statistical analysis suite for advanced analytics, business intelligence and data management.

  • Microsoft Excel

    Software

    Spreadsheet for data entry, basic statistical analysis and report generation.

Certifications

Industry links

Common misconceptions

  • Statistics and computing is just about counting numbers.

    The programme covers probability theory, statistical inference, programming, database systems and computational methods for complex data analysis.

  • Graduates only work in government statistics offices.

    Graduates work in banks, insurance companies, technology firms, research institutions, NGOs and consulting firms as data analysts and statisticians.

  • The programme is the same as computer science.

    The programme combines statistics with computing, focusing on statistical methods and data analysis rather than software engineering.

  • Statistics is becoming obsolete with AI.

    Statistical foundations underpin machine learning and AI, making statistics and computing graduates essential in the data science era.

Related courses

Further reading

Keep this

Fees and entry marks for Bachelor of Science in Statistics and Computing are restated every intake. Save it and the app keeps this version, so you can see what changed when it does.