General entry requirements

Minimum requirements

2:1 undergraduate degree (or equivalent) in Statistics, Mathematics or a science with sufficiently high mathematical content.

English language requirements

You can find out more about our English language requirementsLink opens in a new window. This course requires the following:

• Band A
• No score lower than 6.0 in all IELTS fields with a total score of 6.5 minimum.

International qualifications

We welcome applications from students with other internationally recognised qualifications.

For more information, please visit the international entry requirements pageLink opens in a new window.

Additional requirements

There are no additional entry requirements for this course.

Core modules

Statistical Methods

The module content will include a thorough grounding in classical and Bayesian methods of statistical inference with an introduction to selected modern developments in statistical methodology. Since MSc students have different background knowledge in statistics, we start afresh although a solid mathematical background is assumed. At the end of the course you will have a solid background in basic concepts of statistical methodology and knowledge at an advanced level in some areas.

An Introduction to Statistical Practice

Introduction to Statistical Practice module introduces statistical computing, using R, through hands-on practical classes on the analysis of real data from a variety of scientific and other disciplines; and develops skills such as report-writing, statistical graphics, etc.

Dissertation

After successfully completing the taught part of the programme the student also undertakes a substantial project under the supervision of a Department member, and writes a dissertation reporting the results. Such projects can be in any of the areas covered by the MSc, including applied statistics, statistical methodology, computational methods, probability etc.

Optional modules

The remaining six modules are chosen from a wide range of options, subject to availability, to suit the interests of individual students. The options include:

Advanced Topics in Data Science

This module comprises three selected topics in statistics and computer science. The topics may change from year to year, some examples from previous years have included Deep Learning for Natural Language Processing, Decision Trees and Random Forests, Model Comparison and Selection, Artificial Neural Networks, Introduction to Reinforcement Learning and Modelling the Written Word: Compression and Human-Computer-Interfaces.

Bayesian Forecasting and Intervention with Advanced Topics

Forecasting is a vital prerequisite to decision making. This course offers a very powerful fundamental probabilistic approach to forecasting, controlling and learning about uncertain commercial, financial, economic, production, environmental and medical dynamic systems. The theory will be illustrated by real examples from industry, marketing, finance, government, agriculture etc. A familiarity with the material in this module will be very useful to all students planning a career involving a component of industrial, business or government statistics.

Applied Stochastic Processes with Advanced Topics

This module provides introduction to concepts and techniques which are fundamental in modern applied probability theory and operations research: Models for queues, point processes, and epidemics. Furthermore, you will study notions of equilibrium, threshold behaviour, and description of structure. The ideas presented in this module have a vast range of applications, for example routing algorithms in telecommunications (queues), assessment of apparent spatial order in astronomical data (stochastic geometry), and description of outbreaks of disease (epidemics).

Medical Statistics with Advanced Topics

Modern applications of statistics to medicine are highly developed, and many medical research papers employ statistical techniques. Large numbers of statisticians are employed in medical research establishments, particularly in pharmaceutical companies and medical schools. Medical statistics continues to be a buoyant area for statistical recruitment. The course will explain why and how statistics is used in medicine, and study some of the statistical methods commonly used in medical research. We will include examples from our own research. The statistical techniques applied to medical data are also relevant in other applications.

Monte Carlo Methods

When modelling real world phenomena statisticians are often confronted with the following dilemma: should we choose a standard model that is easy to compute with or use a more realistic model that is not amenable to analytic computations such as determining means and p-values. We are faced with such choice in a vast variety of application areas, some of which we will encounter in this module. These include financial models, genetics, polymer simulation, target tracking, statistical image analysis and missing data problems. With the advent of modern computer technology, we are no longer restricted to standard models as we can use simulation-based inference.

Designed Experiments with Advanced Topics

Designed experiments are used in industry, agriculture, medicine and many other areas of activity to test hypotheses, to learn about processes and to predict future responses. The primary purpose of experimentation is to determine the relationship between a response variable and the settings of a number of experimental variables (or factors) that are presumed to affect it. Experimental design is the discipline of determining the number and order (spatial or temporal) of experimental runs, and the setting of the experimental variables.

Multivariate Statistics with Advanced Topics

Multivariate data arises whenever several interdependent variables are measured simultaneously. Such high-dimensional data is becoming the rule, rather than the exception in many areas including medicine, social and environmental sciences and economics. The analysis of such multidimensional data often presents an exciting challenge that requires new statistical techniques which are usually implemented using computer packages. This module aims to give you a good and rigorous understanding of the geometric and algebraic ideas that these techniques are based on, before giving you a chance to try them out on some real data sets.

For further modules, see here.

Teaching

For the nine-month period from October to June, you will be engaged in attending a set of modules ranging across the spectrum of the most fundamental areas of Statistics and Probability.  

After successfully completing the taught portion of the Master’s you will undertake a dissertation project under supervision of a member of staff.

Assessment

Assessment is initially made for each module separately: some modules have an element of continuous assessment through coursework, but the majority of modules are assessed through written examinations in May and June or, for some modules, January.

Your performance in the core and optional modules combined is then examined by an examinations board consisting of academic staff plus an External Examiner appointed from another university. Dissertations are examined in the Department and then by the External Examiner.

The MSc degree is awarded subject to satisfactory standard in the dissertation and taught modules. Students who do outstandingly well in both taught modules and the dissertation may be awarded the MSc with Distinction or Merit.

Your timetable

Your personalised timetable will be complete when you are registered for all modules, compulsory and optional, and you have been allocated to your lectures, seminars and other small group classes. Your compulsory modules will be registered for you and you will be able to choose your optional modules when you join us.

Your career

Graduates from these courses have gone on to work for employers worldwide including companies such as: Aimia; Thomas Miller; DeLoitte as well as international pharmaceutical industries. Candidates with high distinction marks have gone on to pursue PhD degrees at prestigious universities such as Cambridge, Oxford, Imperial, LSE, etc. or in the US.

Our graduates have pursued roles such as: professional statisticians; actuaries; business, research and administrative professionals; IT business analysts, architects and systems designers; management consultants and business analysts; programmers and software development professionals.

Our department has a dedicated professionally qualified Senior Careers Consultant offering impartial advice and guidance together with workshops and events throughout the year. Previous examples of workshops and events include:

• Warwick careers fairs throughout the year
• Employer presentations within the department (e.g. Pharmaceutical Statistics, Actuarial, Geospatial Analytics)
• Interview skills for Statistics students
• Maths and Stats Careers Fair
• PhD academic and non-academic careers event

Statistics at Warwick

Statistics and probability theory are key to understanding data and underlying processes involving risk and uncertainty.

We also explore applications in a wide array of areas and develop impact of our research in many scientific fields within sciences, social sciences, medicine, engineering, management science, finance, commerce and others.

Founded in October 1972, Warwick Statistics is internationally renowned for its wide-ranging and world-leading research and its innovative undergraduate and postgraduate degree programmes.

Find out more about us on our website.Link opens in a new window

Our Postgraduate courses

• Statistics (MSc)
• Statistics (PhD/MPhil)

Tuition fees

Tuition fees are payable for each year of your course at the start of the academic year, or at the start of your course, if later. Academic fees cover the cost of tuition, examinations and registration and some student amenities.

Find your taught course fees  

Fee Status Guidance

We carry out an initial fee status assessment based on the information you provide in your application. Students will be classified as Home or Overseas fee status. Your fee status determines tuition fees, and what financial support and scholarships may be available. If you receive an offer, your fee status will be clearly stated alongside the tuition fee information.

Do you need your fee classification to be reviewed?

If you believe that your fee status has been classified incorrectly, you can complete a fee status assessment questionnaire. Please follow the instructions in your offer information and provide the documents needed to reassess your status.

Find out more about how universities assess fee status

Additional course costs

As well as tuition fees and living expenses, some courses may require you to cover the cost of field trips or costs associated with travel abroad.

For departmental specific costs, please see the Modules tab on the course web page for the list of core and optional core modules with hyperlinks to our Module Catalogue (please visit the Department’s website if the Module Catalogue hyperlinks are not provided).

Associated costs can be found on the Study tab for each module listed in the Module Catalogue (please note most of the module content applies to 2022/23 year of study). Information about module department specific costs should be considered in conjunction with the more general costs below:

• Core text books
• Printer credits
• Dissertation binding
• Robe hire for your degree ceremony

Scholarships and bursaries

How to apply

The application process for courses that start in September and October 2024 will open on 2 October 2023.

Applications will close on 2 August 2024 for students who require a visa to study in the UK, to allow time to receive a CAS and complete the visa application process.

How to apply for a postgraduate taught course