About this course

Learn the theory and application of statistical methods on this MSc Applied Statistics degree at the University of Southampton. Gain in-depth knowledge and skills in analysing large-scale data to solve problems. You'll graduate ready for a career as a statistician in a wide range of sectors, from government to medicine.

On this UK statistics master’s course we’ll teach you how to collect and analyse quantitative social science data and apply it to real-world problems.

Through your choice of modules you’ll be able to adapt the course to your personal interests or career plans.

Typical subjects include:

survey methods and design
survey modelling (multilevel, longitudinal, linear)
analysing complex data sets

You’ll benefit from the research of our expert academics, whose findings feed directly into the course content. Our main areas of expertise at Southampton include:

sampling
small-area estimation
census and administrative data
analysis of ‘big data’

We’re known for the expertise and international scope of our research and for the application of cutting-edge quantitative and qualitative methods.

We host the National Centre for Research Methods (NCRM), which provides training and capacity building as well as carrying out its own research programme.

Flexible study

If you prefer, you can apply to study this course as:

a part-time master's - study the same course content over 2 or more years

Your modules and fees may vary if you choose a different study option.

Course lead

Your course leader is Dr Olga Maslovskaya, Lecturer in Social Statistics and Demography within Economic, Social and Political Sciences. Her research interests include survey research, survey methodology, social statistics, quantitative research methods and demography. Read Dr Maslovskaya's staff profile to find out more about her work.

Course location

This course is based at Highfield.

Awarding body

This qualification is awarded by the University of Southampton.

Download the programme specification

The programme specification sets out the learning outcomes of this course and details how the course is taught and assessed.

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Download 2021-22 programme specification

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Entry requirements

You’ll need a 2:1 degree in a relevant subject such as:

statistics
quantitative analysis
maths
economics (with emphasis on econometrics)
physical sciences
social sciences (with emphasis on quantitative methods)
geography (with emphasis on quantitative methods)

We’ll also consider non-graduate qualifications, such as the Graduate Diploma of the Royal Statistical Society. Details of statistical training will help us assess your suitability.

Find the equivalent international qualifications for your country.

English language requirements

If English isn't your first language, you'll need to complete an International English Language Testing System (IELTS) to demonstrate your competence in English. You'll need all of the following scores as a minimum:

IELTS score requirements

overall score: 6.5
reading: 5.5
writing: 5.5
speaking: 5.5
listening: 5.5

We accept other English language tests. Find out which English language tests we accept.

Got a question?

Please contact us if you're not sure you have the right experience or qualifications to get onto this course.

Email: enquiries@southampton.ac.uk
Tel: +44(0)23 8059 5000

Course structure

You’ll study for a full 12 months, from September to the following September.

In the week before the start of semester 1, you’ll attend a 4-day induction course which will introduce you to our computer and library facilities.

For the first 9 months (semesters 1 and 2) you’ll study the taught part of the course. This is made up of modules that everyone on the course takes and modules that we’ll ask you to choose from a list of options.

Exams take place at the end of semesters 1 and 2.

You’ll spend the last 3 months of the course working independently on your research project and dissertation.

Want more detail? See all the modules in the course.

Modules

For entry in Academic Year 2021-22

You must study the following modules:

Analysis of Hierarchical (Multilevel & Longitudinal) Data

This module introduces students to the main statistical modelling approaches that can handle hierarchical data structures. The module has mainly an applied scope where basic theory is introduced to ensure understanding. Practical computer sessions using M...

Complex Survey Data Analysis

The aim of this module is to provide an introduction to the finite-population inference and modelling approaches for survey data.

Dissertation

This module will provide you with guidance and support throughout the writing of your dissertation. From discussing your initial ideas of your dissertation through the process of actually writing the document, this module will provide you with the informa...

Generalised Linear Models

This module aims to introduce students to a wide range of statistical models grouped by the unifying theory of Generalized Linear Models: Linear, Logistic, Multinomial, Cumulative Ordinal and Poisson regression, as well as Log-linear models are presented,...

Likelihood and Bayesian Inference

This module develops methods for conducting inference about parametric statistical models. The techniques studied are general and applicable to a wide range of statistical models, including simple models for identically distributed responses and regressio...

Research Communication Skills

This module focuses on practical aspects of research communication skills including oral presentation, scientific report writing, and statistical and demographic consulting.

Sampling Techniques

The aim of this module is to introduce you to the statistical aspects associated with the design and analysis of sample surveys, and to develop your understanding of the principles and methods used to design survey sampling schemes. Basic theory underpinn...

Statistical Computing

This module consists of lecturers and associated practical sessions. The first part will focus on basic statistical programming in R. The second part will provide an introduction to some modern computational statistical methods and their implementation in...

You must also choose from the following modules:

Bayesian Methods

This module will consolidate the basic concepts of Bayesian inference covered in Statistical Theory or MATH3044 Statistical Inference. Students will be introduced to more advanced Bayesian methodology, and to the analysis of data using Bayesian methods.

Demographic Methods 2

The module will cover a range of more advanced methods of demographic analysis, including multiple decrement life tables, health expectancies, an introduction to event history analysis, the use of type 1 and type 2 rates in demography and sources of bias ...

Demographic Methods I

This Module provides an introduction to the technical basis of demography. It focuses on concepts and methods underpinning demographic analysis and provides a practical introduction for those professionally engaged with demographic work (in government de...

Design of Experiments

When planning experiments, it is essential that the data collected are as relevant and informative as possible. The statistical principles for the design of experiments include the choice of optimal or good treatments sets and appropriate replication of t...

Epidemiological Methods

This module introduces students to the main concepts involved in epidemiological analyses. The main epidemiological study designs are introduced and two lectures focus on methods used to analyse case-control studies whilst another two focus on cohort stu...

Evaluation and Monitoring

The aim of this module is to develop students' understanding of the nature of studies to monitor and evaluate intervention programmes, using examples from Government and other related areas. There is a particular focus on the contribution of statistical m...

Key Topics in Social Science: Measurement and Data

This module introduces key sources of social science data (both UK and non-UK), and the measurement of key concepts using these data, within a range of substantive areas. In doing so it focuses on the analysis of a number of fundamental social issues – i...

Philosophy of Social Science Research

This module will look at the dominant traditions in the philosophy of social science and how these have shaped substantive research within the study of the social sciences.

Qualitative Methods 1

The syllabus for this 10 CATS module will cover an introduction to qualitative methods and a range of qualitative data collection methods. We will consider the defining characteristics of qualitative research and its epistemological underpinnings. The ...

Statistical Genetics

Statistical genetics has played a pivotal role in the discovery of genes that cause disease in humans. This module introduces the basic concepts and terms in genetics and demonstrates the use of statistical models to identify disease genes in humans.

Survey Design

Students taking this module will gain first hand experience in the design and management of survey research projects.

Survival Analysis

The module will introduce the basic concepts of survival analysis and to describe and explain how survival analysis can be applied to medical data in other application areas, with emphasis on the use of appropriate statistical software.

Learning and assessment

Learning

The learning activities for this course include the following:

lectures
seminars
group work
projects
independent learning (studying on your own)

Assessment

We’ll assess you through:

essays
a dissertation
presentations
seminar discussions
written exams

Dissertation

You’ll start your supervised research in June and submit a 15,000-word dissertation in September. This will be on a subject of your choice, to be agreed with your tutor.

The dissertation is a chance for you to show in-depth knowledge of a chosen topic.

Past topics include:

statistical methods for social networks
multilevel models of class context on voters at the 1983 General Election
estimation of pay distributions from new earnings survey data
comparing asset with money metric-based measures of poverty in Malawi

You’ll have regular support meetings with your supervisor throughout the process.

Academic Support

You’ll be assigned a personal academic tutor and have access to a senior tutor.

Careers

This degree will qualify you to work as a statistician in a range of sectors, including:

government
medicine
social research
private sector data analytics

You’ll also be in a great position to continue your studies at PhD level.

Careers services at Southampton

We're a top 20 UK university for employability (QS Graduate Employability Rankings 2020). Our Careers and Employability Service will support you throughout your time as a student and for up to 5 years after graduation. This support includes:

work experience schemes
CV/resume and interview skills workshops
networking events
careers fairs attended by top employers
a wealth of volunteering opportunities
study abroad and summer school opportunities

We have a thriving entrepreneurship culture. You'll be able to take advantage of:

our dedicated start-up incubator, Futureworlds
a wide variety of enterprise events run throughout the year
our partnership in the world’s number 1 business incubator, SETsquared

Fees, costs and funding

Tuition fees

Fees for a year's study:

UK students pay £9,250.
EU and international students pay £19,850.

Check fees for other versions of this course.

What your fees pay for

Your tuition fee covers the full cost of tuition and any exams.

Find out how to pay your tuition fees.

Accommodation and living costs, such as travel and food, are not included in your tuition fees. Explore:

10% alumni discount

If you’re a graduate of the University of Southampton you get a 10% discount on your postgraduate tuition fees.

Postgraduate Master’s Loans (UK nationals only)

This can help with course fees and living costs while you study a postgraduate master's course. Find out if you're eligible.

Funding your postgraduate studies

A variety of additional scholarships, grants and bursaries may be available to help you fund your master’s study, both from the University and from other organisations.

Funding for EU and international students

Find out about funding you could get as an international student.

How to apply

Use the 'apply for this course' button on this page to take you to our online application form.
Search for the course you want to apply for.
Complete the application form and upload any supporting documents.
Submit your application.

Application deadlines

UK students

Applications must be received no later than 4 weeks before the start of the course. You must supply all supporting documentation at least 2 weeks before starting your course.

International students

We recommend you apply at least 6 weeks before the start of the course to ensure you're able to meet our requirements and apply for a visa in time.

We cannot guarantee students who do not meet these deadlines will be able to begin their course.

Application assessment fee

We’ll ask you to pay a £50 application assessment fee if you’re applying for any postgraduate taught course that starts in or after September 2021.

This is an extra one-off charge which is separate to your tuition fees. It covers the work and time it takes us to assess your application. You’ll be prompted to pay when you submit your application which won’t progress until you've paid.

If you're a current or former University of Southampton student, or if you're applying for a Master of Research (MRes) degree, you will not need to pay the fee. Find out if you’re exempt on our terms and conditions page.

Supporting information

When you apply you’ll need to submit a personal statement explaining why you want to take the course.

You’ll need to include information about:

your knowledge of the subject area
why you want to study a postgraduate qualification in this course
how you intend to use your qualification

You'll also need to send 2 academic references.

Please include the required paperwork showing your first degree and your IELTS English language test score (if you are a non-native English speaker) with your application. Without these, your application may be delayed.

Learn more about how to apply with our postgraduate application guide.