Science

Doctor of Philosophy in Social Statistics

The Doctor of Philosophy in Social Statistics is a postgraduate research programme offered at the University of Nairobi and Kenyatta University through their respective departments of mathematics and statistics. The programme trains scholars to conduct advanced research on statistical methods for social data, survey methodology, demographic analysis, and social indicators, contributing to evidence-based social policy in Kenya and globally.

Students engage with advanced statistical theory, survey methodology, demographic statistics, social indicators, econometrics, and research methodology. The programme combines coursework with thesis research, requiring candidates to develop a research proposal, conduct independent statistical research, and produce a doctoral dissertation that makes an original contribution to social statistics.

Kenya's development planning, policy evaluation, and monitoring of the Sustainable Development Goals depend on reliable social statistics. The programme addresses national priorities under Vision 2030 by training researchers who can improve social data collection, analysis, and use for national development.

Teaching methods include lectures, statistical computing, survey design and analysis, demographic modelling, and supervised thesis work. Students have access to UoN's School of Mathematics and KU's School of Pure and Applied Sciences, and collaborate with the Kenya National Bureau of Statistics, UNFPA, the World Bank, and government ministries.

Graduates pursue careers as university lecturers, statisticians, demographic analysts, social researchers, and data scientists in universities, KNBS, KEMRI, the World Bank, UN agencies, and government.

This programme is ideal for holders of a Master's degree in social statistics, statistics, demography, or related quantitative fields who are committed to advancing knowledge in social statistics.

Duration: 3-5 years
Public, up to: Ksh 428,000
Private, up to: Ksh 150,000
Job market: High

The programme

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

Practicalities

Study mode: Full-time
Attachment: 0 months
Average class: 6 students
Award: PhD

What you study

10 subjects

Advanced Statistical Theory
Survey Methodology
Demographic Statistics
Social Indicators
Econometrics
Research Methodology
Sampling Theory
Thesis Research
Biostatistics
Data Analysis

Modules

12 in the programme

Advanced Statistical Inference
Year 1Semester 13 creditsCore
Advanced statistical inference including estimation, hypothesis testing, Bayesian methods, and asymptotic theory
Advanced Social Statistics and Statistical Inference
Year 1Semester 13 creditsCore
Social statistics, including probability theory, hypothesis testing, regression analysis, and statistical software applications for doctoral research.
Survey Methodology and Sampling
Year 1Semester 23 creditsCore
Survey design and sampling including probability sampling, sample size determination, non-response, and survey errors
Demographic Methods and Population Projections
Year 1Semester 23 creditsCore
Demographic methods, requiring students to apply theoretical knowledge to real-world problems, conduct independent research, and present findings in a scholarly format.
Demographic Statistics and Modelling
Year 1Semester 33 creditsCore
Demographic methods including life tables, population projections, fertility and mortality estimation, and demographic accounting
Survey Methodology and Sampling Design
Year 1Semester 33 creditsCore
Survey methodology, covering design principles, methodologies, and practical approaches to creating effective solutions in professional contexts.
Social Indicators and Measurement
Year 2Semester 13 creditsCore
Measurement of social indicators including poverty, inequality, education, health, and gender statistics
Statistical Modelling and Regression Analysis
Year 2Semester 13 creditsCore
Statistical modelling, including probability theory, hypothesis testing, regression analysis, and statistical software applications for doctoral research.
Econometrics and Social Data Analysis
Year 2Semester 23 creditsCore
Econometric methods including regression, panel data, and causal inference for social research
Bayesian Statistics and Computational Methods
Year 2Semester 23 creditsCore
Bayesian statistics, including probability theory, hypothesis testing, regression analysis, and statistical software applications for doctoral research.
Categorical Data and Multivariate Methods
Year 2Semester 33 creditsCore
Analysis of categorical data, multivariate methods, and latent variable models for social statistics
Research Methods in Social Statistics
Year 2Semester 33 creditsCore
Research methods, covering quantitative and qualitative approaches, data collection techniques, and analytical frameworks relevant to doctoral-level research in the field.

Specialisations

Public Health Data Analysis (Junior)
Specialization in Public Health Data Analysis (Junior), preparing graduates for careers such as public-health-data-analyst-junior.
Biostatistics Research
Specialization in Biostatistics Research, preparing graduates for careers such as biostatistician.
Academic Research in Science
Specialization in Academic Research in Science, preparing graduates for careers such as university-lecturer.
Public Health Data Analysis
Specialization in Public Health Data Analysis, preparing graduates for careers such as data-analyst-in-public-health.
Social Data Science
Specialization in Social Data Science, preparing graduates for careers such as social-data-scientist.
Economic Data Science
Specialization in Economic Data Science, preparing graduates for careers such as economic-data-scientist.
Bayesian Methods
Research on Bayesian methods
Demographic Statistics
Research on demographic statistics
Social Indicators
Research on social indicators
Survey Methodology
Research on survey methodology

A day as a student

A typical day combines statistical analysis of social data with survey methodology, demographic modelling, data analysis, literature review, and thesis writing. Students attend statistics research seminars, present findings at colloquia, and engage with KNBS and UNFPA for social statistics research.

The trade offs

In its favour

Access to KNBS, Ministry of Planning and UN agencies
Two public universities offer the programme providing choice and fee range
Skills applicable across all sectors
Diverse career paths in academia, government, international organisations, and data science

Against it

Requires strong mathematical and computing skills
UoN fees are high at KES 432,000 per year
Access to quality social data can be limited
Statistical research requires continuous updating of methods and software skills

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

Public337k to 428k

337k at Kenyatta University428k at University of Nairobi

Private150k to 150k

150k at Mount Kenya University150k at Mount Kenya 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

UoN 428K/yr (uonbi Math), KU 336.6K/yr (ku.ac.ke). MKU 150K/yr (mku.ac.ke).

Students may access HELB postgraduate loans, DAAD scholarships, NRF research grants, and ISI research grants for social statistics research.

Funding options

HELB Postgraduate Loan
LoanKsh 80,000
DAAD Scholarship
Scholarship
NRF Research Grant
Grant
ISI Research Grant
Grant

Scholarships

5 recorded

HELB Postgraduate Scholarship
LoanKsh 200,000Kenyan
Kenyan postgraduate students
DAAD Kenya Scholarship
ScholarshipKenyan
Postgraduate students in Kenya
NACOSTI Research Grant
GrantKenyan
Science and technology researchers in Kenya
DAAD Scholarship
ScholarshipKenyan
African graduates meeting academic criteria for doctoral study
HELB Postgraduate Loan
LoanKsh 80,000Kenyan
Kenyan postgraduate students enrolled in recognised universities

Getting in

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

What you need

KCSE mean grade: C+
Alternative entry: Relevant diploma or equivalent qualification

Master's Degree
MSc in Social Statistics, Statistics, Demography, or related quantitative field from a recognised university
Undergraduate qualification
Bachelor's degree in Statistics, Mathematics, or related quantitative field
Research capability
Evidence of research ability through publications, reports, or academic work

How you are assessed

5 components

Thesis Proposal Defence
Oral defence20% of the mark
Defence of research proposal before faculty panel
Coursework
Continuous assessment30% of the mark
Assignments, data analysis projects and seminar presentations
Thesis
Thesis50% of the mark
Doctoral thesis research, submission and oral defence
Oral Viva Voce
Coursework100% of the mark
Thesis Examination
Coursework100% of the mark

Accreditation

Accredited by the Commission for University Education (CUE).

Accredited by

Commission for University Education (CUE)
Academic accreditationRequired
Mandatory accreditation for all university programmes in Kenya
Commission for University Education
AcademicRequired
Statutory body responsible for accreditation of university programmes in Kenya

Where it leads

The roles it opens, and what you leave with.

Where graduates go

8 roles

Survey Statistician
High demandKsh 250,000 to Ksh 600,000
Survey design at KNBS and research firms
Demographic Analyst
Moderate demandKsh 220,000 to Ksh 550,000
Demography at NCPD and UN agencies
Social Statistician
High demandKsh 220,000 to Ksh 550,000
Statistics at KNBS and research institutes
University Professor
High demandKsh 200,000 to Ksh 500,000
Teaching and research in statistics departments
University Lecturer (Statistics)
High demandKsh 90,000 to Ksh 200,000
Teaches statistics and conducts research in university mathematics and statistics departments
Demographer
Moderate demandKsh 80,000 to Ksh 180,000
Analyses population trends and projections at KNBS, UNFPA, or research institutions
Statistician
High demandKsh 90,000 to Ksh 200,000
Analyses social data at KNBS, KEMRI, or research institutions
Data Scientist
High demandKsh 100,000 to Ksh 250,000
Applies statistical methods to social and economic data in industry, government, or consulting

Graduate outcomes

Graduates work as university lecturers, statisticians, demographic analysts, and data scientists in universities, KNBS, KEMRI, the World Bank, UN agencies, and government.

Where these fields lead

8 careers

Certifications

Industry links

Common misconceptions

Social statistics is just about collecting numbers on people
Social statistics involves advanced survey design, sampling theory, demographic modelling, and statistical analysis to inform social policy and research.
A PhD in social statistics has limited career prospects
KNBS, UN agencies, the World Bank, and government ministries need social statisticians for census, surveys, and policy evaluation.
Social statistics is not relevant to Kenya
Kenya's development planning and monitoring of SDGs require high-quality social statistics, making this research critical for national development.
Social statistics is the same as general statistics
Social statistics applies statistical methods specifically to social, demographic, and economic data, with a focus on survey and population data.

Related courses

Doctor of philosophy in mathematical statistics