PhD in Statistics 36 months PHD Programme By The University of Warwick |TopUniversities
Subject Ranking

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Programme Duration

36 monthsProgramme duration

Tuitionfee

25,920 GBPTuition Fee/year

Main Subject Area

Statistics and Operational ResearchMain Subject Area

Programme overview

Main Subject

Statistics and Operational Research

Degree

PhD

Study Level

PHD

Study Mode

On Campus

The MPhil/PhD course is Statistics is delivered by the CDT in Statistics. Unlike many CDTs, this is not dedicated to a single topic, but covers the range of research areas within probability and statistics, to include theoretical and applied probability, mathematical finance, statistical machine learning, computational, methodological, and applied statistics. Our vision is to create a thorough training environment that allows you to develop both depth and breadth of knowledge and skills and fosters innovative and interdisciplinary thinking. We have a dedicated training programme in the first year, designed to optimally prepare you for your PhD project work and opportunities for continuing development through the years. 

For the CDT in Statistics, first-year training is split into two parts: a common core, aiming to provide you with an overview of research topics and activity in all areas represented within the department as well as to develop fundamental research skills and an optional core, allowing you to choose from a wide range of advanced graduate modules, designed for PhD students. This optimally prepares you for the specialised work of the PhD project under the supervision of individual faculty members. You will choose your supervisor and research topic during the first year of the programme. PhD training that is not via the CDT and where the student works with a nominated supervisor from day one is available only in cases where this training scheme is required by the student’s funding source.

Programme overview

Main Subject

Statistics and Operational Research

Degree

PhD

Study Level

PHD

Study Mode

On Campus

The MPhil/PhD course is Statistics is delivered by the CDT in Statistics. Unlike many CDTs, this is not dedicated to a single topic, but covers the range of research areas within probability and statistics, to include theoretical and applied probability, mathematical finance, statistical machine learning, computational, methodological, and applied statistics. Our vision is to create a thorough training environment that allows you to develop both depth and breadth of knowledge and skills and fosters innovative and interdisciplinary thinking. We have a dedicated training programme in the first year, designed to optimally prepare you for your PhD project work and opportunities for continuing development through the years. 

For the CDT in Statistics, first-year training is split into two parts: a common core, aiming to provide you with an overview of research topics and activity in all areas represented within the department as well as to develop fundamental research skills and an optional core, allowing you to choose from a wide range of advanced graduate modules, designed for PhD students. This optimally prepares you for the specialised work of the PhD project under the supervision of individual faculty members. You will choose your supervisor and research topic during the first year of the programme. PhD training that is not via the CDT and where the student works with a nominated supervisor from day one is available only in cases where this training scheme is required by the student’s funding source.

Admission Requirements

120+
6.5+
180+
62+
92+
2:1 undergraduate degree (or equivalent) in Statistics, Mathematics or a science with sufficiently high mathematical content.

3 Years
Oct

Tuition fees

Domestic
5,206 GBP
International
25,920 GBP

Scholarships

Selecting the right scholarship can be a daunting process. With countless options available, students often find themselves overwhelmed and confused. The decision can be especially stressful for those facing financial constraints or pursuing specific academic or career goals.

To help students navigate this challenging process, we recommend the following articles:

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