Technology

Bachelor of Science in Applied Statistics with Computing

The Bachelor of Science in Applied Statistics with Computing is a degree programme that combines statistical methods with computing skills to prepare graduates for careers in data analysis, statistical modelling and computational statistics. The programme is offered at multiple Kenyan universities including Moi University, University of Eldoret, Karatina University and Garissa University.

The curriculum covers probability theory, statistical inference, regression analysis, programming, data structures, database systems, statistical computing, sampling methods, time series analysis, Bayesian statistics, operations research, research methods, data mining and quality control. Students develop competencies in both statistical theory and computational applications.

Throughout the programme, students engage in lectures, laboratory practicals, programming projects, data analysis assignments, industrial attachment and a research project. The practical approach ensures graduates can collect, analyse and interpret data using computational tools, build statistical models and apply computing skills to solve statistical problems.

The programme emphasises the integration of statistics with computing, recognising that modern data analysis requires professionals who can combine statistical knowledge with programming and database management skills. Students learn about statistical software, data management, computational methods and the application of computing to statistical analysis.

Graduates are equipped to work in government agencies, financial institutions, research organisations, insurance companies, technology firms, healthcare organisations, non-governmental organisations and consulting firms. They contribute to data analysis, statistical modelling, business intelligence and data-driven decision-making.

Career opportunities exist in government ministries, commercial banks, insurance companies, research institutions, technology companies and consulting firms. Graduates work as statistical analysts, data analysts, biostatisticians, research analysts and quantitative analysts across sectors requiring statistical and computing expertise.

Duration: 4 years
Public, up to: Ksh 307,000
Private, up to: Ksh 500,000
Job market: Moderate

The programme

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

Practicalities

Study mode: Full-time
Attachment: 3 months
Average class: 40 students
Award: Bachelor

What you study

10 subjects

Probability Theory
Statistical Inference
Regression Analysis
Programming
Data Structures
Database Systems
Statistical Computing
Sampling Methods
Time Series Analysis
Research Methods

Modules

12 in the programme

Cell Biology and Genetics
Year 1Semester 13 creditsCore
Cell structure, function, division, DNA replication, gene expression, and inheritance.
Foundations of the Discipline
Year 1Semester 13 creditsCore
Foundations of the Discipline: Introduction to core concepts, theories, and principles of the field. Covers theoretical foundations, practical applications, and industry-relevant skills.
General Chemistry
Year 1Semester 23 creditsCore
Atomic structure, bonding, stoichiometry, states of matter, and chemical reactions.
Research Methods
Year 1Semester 23 creditsCore
Quantitative and qualitative research methodologies, data collection, and analysis techniques.
Mathematics for Sciences
Year 1Semester 33 creditsCore
Mathematics for Sciences: Calculus, algebra, trigonometry, and statistical methods for science students. Covers theoretical foundations, problem-solving techniques, and practical applications.
Physics for Sciences
Year 2Semester 13 creditsCore
Mechanics, waves, electricity, optics, and modern physics for science programmes.
Microbiology
Year 2Semester 23 creditsCore
Microbial structure, metabolism, genetics, cultivation, and applied microbiology.
Research Methods and Statistics
Year 2Semester 33 creditsCore
Research Methods and Statistics: Scientific research methodology, experimental design, and statistical analysis. Covers quantitative and qualitative approaches, data collection, analysis, and repor...
Laboratory Techniques and Safety
Year 3Semester 13 creditsCore
Laboratory Techniques and Safety: Laboratory procedures, instrumentation, safety protocols, and quality control. Covers safety regulations, risk assessment, and workplace hazard management.
Environmental Science
Year 3Semester 23 creditsCore
Environmental Science: Ecosystems, biodiversity, environmental pollution, and conservation. Covers ecosystem dynamics, conservation principles, and environmental management practices.
Industrial Attachment
Year 3Semester 33 creditsCore
Industrial Attachment: Supervised attachment at research institutions, laboratories, or industry. Provides hands-on industry experience, mentorship, and professional skills development.
Research Project
Year 4Semester 16 creditsCore
Research Project: Independent research project culminating in a defended report. Involves independent research, data analysis, and scholarly writing under supervision.

Specialisations

Biostatistics
Focus on 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.
Data Analytics
Specialisation in data mining, exploratory data analysis and business intelligence. 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.
Statistical Computing
Concentration on computational methods, statistical programming and simulation. 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.
Economic Statistics
Focus on economic data analysis, national accounts and economic indicators. 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.
Quality Control and Assurance
Specialisation in statistical process control, quality management and reliability analysis. 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.
General Practice
Broad foundational knowledge covering core principles and practices in the field. 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.
Research and Analysis
Focus on research methods, data analysis, and evidence-based decision making. 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.
General Practice
Broad foundational knowledge covering core principles and practices in the field. 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.
Research and Analysis
Focus on research methods, data analysis, and evidence-based decision making. 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 lectures on probability theory and regression analysis, writing R or Python code for statistical computing assignments, working with real datasets to build statistical models and practising database queries for data management.

The trade offs

In its favour

Combines statistics with computing, providing versatile skills in high demand across sectors.
Accredited by the Commission for University Education (CUE).
Offered at multiple universities across Kenya, providing institution choice.
Graduates are eligible for HELB loans and government funding.
Strong foundation for postgraduate study in statistics, data science or analytics.

Against it

Limited programme specialisation options may be available.
Competitive job market requiring practical experience and networking.
Requires strong mathematical and analytical aptitude.

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

Public306k to 307k

306k at Kenyatta University307k at University of Nairobi

Private219k to 500k

219k at Kabarak University500k at Strathmore University

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

KU Stats&Prog 306K/yr (mawese). UoN ~307K/yr. Kabarak 218.7K, Strathmore ~500K/yr (truematch).

Students can access HELB undergraduate loans, Universities Fund government scholarships and county government bursaries.

Funding options

HELB Undergraduate Loan
Universities Fund Government Scholarship
County Government Bursaries

Scholarships

3 recorded

Higher Education Loans Board (HELB) Loan
LoanKsh 60,000Kenyan
Kenyan students admitted to recognised universities demonstrating financial need.
County Government Bursaries
GrantKsh 50,000Kenyan
Students from specific counties. Criteria vary by county.
Higher Education Fund (HEF)
GrantKsh 200,000Kenyan
Government-sponsored (KUCCPS) students in public universities. Awarded through the Higher Education Funding Model.

Getting in

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

What you need

KCSE mean grade: C+ (Plus) mean grade at KCSE
Alternative entry: KNEC Diploma in Applied Statistics or equivalent from a recognised institution.

How you are assessed

5 components

Continuous Assessment Tests and Assignments
Coursework30% of the mark
Written tests, assignments, and practical exercises throughout the semester.
Continuous Assessment Tests and Practicals
Coursework30% of the mark
Written tests, programming assignments, statistical computing practicals and data analysis projects throughout the semester.
End of Semester Examinations
Examination50% of the mark
Comprehensive written and practical examinations covering statistics theory and computing concepts.
Industrial Attachment Report
Practicum10% of the mark
Supervised attachment with a data-driven organisation, assessed through logbook and written report.
Research Project
Project10% of the mark
Independent research project applying statistical methods with computing, including data analysis and written report.

Accreditation

Accredited by the Commission for University Education (CUE). The programme is offered at Moi University, University of Eldoret, Karatina University, Garissa University and other CUE-accredited universities.

Accredited by

Commission for University Education (CUE)
NationalRequired
CUE accredits all university programmes in Kenya. This programme must be offered by a CUE-accredited university.

Where it leads

The roles it opens, and what you leave with.

Where graduates go

8 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.
Statistical Analyst
High demandKsh 55,000 to Ksh 120,000
Applies statistical methods to analyse data and generate insights for research institutions, government agencies or businesses.
Data Analyst
Very high demandKsh 60,000 to Ksh 130,000
Collects, cleans and analyses data using statistical and computing tools to support decision-making in organisations.
Biostatistician
Moderate demandKsh 60,000 to Ksh 125,000
Applies statistical methods to health research, clinical trials and epidemiological studies in research institutions.
Research Analyst
Moderate demandKsh 50,000 to Ksh 100,000
Conducts statistical analysis for research institutions, supporting study design and data interpretation.

Graduate outcomes

Graduates work as statistical analysts, data analysts, biostatisticians, research analysts and quantitative analysts in government agencies, financial institutions, research organisations and technology firms.

Where these fields lead

8 careers

Tools you will learn

R
SoftwarePrimary
Programming language for statistical computing and data analysis.
Python
Programming languagePrimary
Programming language for data analysis, statistical computing and automation.
SAS
Software
Statistical analysis software for advanced analytics and business intelligence.
SPSS
Software
Statistical analysis software for survey data and social science research.
SQL
Software
Query language for database management and data extraction.
Microsoft Excel
Software
Spreadsheet for data management, statistical analysis and reporting.

Certifications

Industry links

Common misconceptions

Applied Statistics with Computing is just about numbers and formulas.
The programme combines statistics with programming, database management and computational methods to solve real-world data problems.
Graduates only work as statisticians in government offices.
Graduates work as data analysts, statistical analysts and quantitative analysts in banks, insurance companies, technology firms and research institutions.
The programme does not require programming skills.
Programming in R and Python is a core component, essential for statistical computing and data analysis.
Applied Statistics with Computing is the same as Computer Science.
The programme focuses on statistical methods with computing as a tool, while Computer Science focuses on software development and systems design.