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Develop the skills and knowledge a professional statistician needs to solve problems across a range of career paths.
Our MSc Statistics course will teach you the theories behind a variety of statistical techniques and how to apply them in scenarios that professional statisticians face every day.
Statistical skills open all kinds of doors, and through our MSc Statistics course you’ll develop the knowledge and experience needed for roles spanning finance and consultancy, healthcare, data science, public administration and research.
Whether you want to advance your understanding of the topics you found most interesting during your undergraduate studies or gain the skills needed to achieve your goals, you’ll develop a detailed working knowledge of important statistical techniques and concepts.
You’ll explore topics including linear and generalised linear modelling, Bayesian statistics, time series and machine learning. You’ll learn how to collect data and design experiments, and the role of statistics in clinical trials. You’ll also develop the ability to analyse and draw meaningful conclusions from data, and grow your programming skills using the statistical computing software R.
You’ll spend around a third of your time working on your dissertation, under the supervision of an active researcher who is an expert in their field. This may focus on investigating a data set, or a more theoretical or methodological topic. You’ll blend theoretical knowledge with practical skills, mastering project planning, data acquisition, problem specification and analysis skills. You’ll also learn how to present statistical information, and gain experience communicating your findings verbally and in writing.
Examples of recent dissertation topics include:
Spatio-temporal Modelling of Social Phenomena
Feature selection for high dimensional data
Modelling Sports Results
Neural Networks with Python
Dissertation topics are often provided by external clients, such as pharmaceutical companies or sports modelling organisations. Distance learning students also often come with projects designed by their employer.
Accreditation
This course is accredited by the Royal Statistical Society
Programme overview
Main Subject
Statistics and Operational Research
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Develop the skills and knowledge a professional statistician needs to solve problems across a range of career paths.
Our MSc Statistics course will teach you the theories behind a variety of statistical techniques and how to apply them in scenarios that professional statisticians face every day.
Statistical skills open all kinds of doors, and through our MSc Statistics course you’ll develop the knowledge and experience needed for roles spanning finance and consultancy, healthcare, data science, public administration and research.
Whether you want to advance your understanding of the topics you found most interesting during your undergraduate studies or gain the skills needed to achieve your goals, you’ll develop a detailed working knowledge of important statistical techniques and concepts.
You’ll explore topics including linear and generalised linear modelling, Bayesian statistics, time series and machine learning. You’ll learn how to collect data and design experiments, and the role of statistics in clinical trials. You’ll also develop the ability to analyse and draw meaningful conclusions from data, and grow your programming skills using the statistical computing software R.
You’ll spend around a third of your time working on your dissertation, under the supervision of an active researcher who is an expert in their field. This may focus on investigating a data set, or a more theoretical or methodological topic. You’ll blend theoretical knowledge with practical skills, mastering project planning, data acquisition, problem specification and analysis skills. You’ll also learn how to present statistical information, and gain experience communicating your findings verbally and in writing.
Examples of recent dissertation topics include:
Spatio-temporal Modelling of Social Phenomena
Feature selection for high dimensional data
Modelling Sports Results
Neural Networks with Python
Dissertation topics are often provided by external clients, such as pharmaceutical companies or sports modelling organisations. Distance learning students also often come with projects designed by their employer.
Accreditation
This course is accredited by the Royal Statistical Society
Admission Requirements
Minimum 2:1 undergraduate honours degree in a relevant subject with relevant modules. We look for applications that demonstrate background within mathematics (particularly calculus and linear algebra), probability (and/or stochastic processes) and statistics (eg Linear modelling, multivariate methods, machine learning, time series etc). Typically we require a selection of modules from each of the three areas to cover each year of undergraduate study and at least 50% of the degree to be in a mathematical subject. Applications with employment history in statistical or data science fields are also welcomed, including for distance learning courses. In such cases we consider the balance of both relevant parts of the employment history and academic qualifications. English language requirements: IELTS 6.5 (with 6 in each component) or University equivalent.
1 Year
Sep
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:
Statistics MSc
Western Bank, Sheffield,, United Kingdom
# 101-150QS Subject Rankings
12 monthsProgramme duration
Statistics and Operational ResearchMain Subject Area
Programme overview
Main Subject
Statistics and Operational Research
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Develop the skills and knowledge a professional statistician needs to solve problems across a range of career paths.
Our MSc Statistics course will teach you the theories behind a variety of statistical techniques and how to apply them in scenarios that professional statisticians face every day.
Statistical skills open all kinds of doors, and through our MSc Statistics course you’ll develop the knowledge and experience needed for roles spanning finance and consultancy, healthcare, data science, public administration and research.
Whether you want to advance your understanding of the topics you found most interesting during your undergraduate studies or gain the skills needed to achieve your goals, you’ll develop a detailed working knowledge of important statistical techniques and concepts.
You’ll explore topics including linear and generalised linear modelling, Bayesian statistics, time series and machine learning. You’ll learn how to collect data and design experiments, and the role of statistics in clinical trials. You’ll also develop the ability to analyse and draw meaningful conclusions from data, and grow your programming skills using the statistical computing software R.
You’ll spend around a third of your time working on your dissertation, under the supervision of an active researcher who is an expert in their field. This may focus on investigating a data set, or a more theoretical or methodological topic. You’ll blend theoretical knowledge with practical skills, mastering project planning, data acquisition, problem specification and analysis skills. You’ll also learn how to present statistical information, and gain experience communicating your findings verbally and in writing.
Examples of recent dissertation topics include:
Dissertation topics are often provided by external clients, such as pharmaceutical companies or sports modelling organisations. Distance learning students also often come with projects designed by their employer.
Accreditation
This course is accredited by the Royal Statistical Society
Programme overview
Main Subject
Statistics and Operational Research
Degree
MSc
Study Level
Masters
Study Mode
On Campus
Develop the skills and knowledge a professional statistician needs to solve problems across a range of career paths.
Our MSc Statistics course will teach you the theories behind a variety of statistical techniques and how to apply them in scenarios that professional statisticians face every day.
Statistical skills open all kinds of doors, and through our MSc Statistics course you’ll develop the knowledge and experience needed for roles spanning finance and consultancy, healthcare, data science, public administration and research.
Whether you want to advance your understanding of the topics you found most interesting during your undergraduate studies or gain the skills needed to achieve your goals, you’ll develop a detailed working knowledge of important statistical techniques and concepts.
You’ll explore topics including linear and generalised linear modelling, Bayesian statistics, time series and machine learning. You’ll learn how to collect data and design experiments, and the role of statistics in clinical trials. You’ll also develop the ability to analyse and draw meaningful conclusions from data, and grow your programming skills using the statistical computing software R.
You’ll spend around a third of your time working on your dissertation, under the supervision of an active researcher who is an expert in their field. This may focus on investigating a data set, or a more theoretical or methodological topic. You’ll blend theoretical knowledge with practical skills, mastering project planning, data acquisition, problem specification and analysis skills. You’ll also learn how to present statistical information, and gain experience communicating your findings verbally and in writing.
Examples of recent dissertation topics include:
Dissertation topics are often provided by external clients, such as pharmaceutical companies or sports modelling organisations. Distance learning students also often come with projects designed by their employer.
Accreditation
This course is accredited by the Royal Statistical Society
Admission Requirements
We look for applications that demonstrate background within mathematics (particularly calculus and linear algebra), probability (and/or stochastic processes) and statistics (eg Linear modelling, multivariate methods, machine learning, time series etc). Typically we require a selection of modules from each of the three areas to cover each year of undergraduate study and at least 50% of the degree to be in a mathematical subject.
Applications with employment history in statistical or data science fields are also welcomed, including for distance learning courses. In such cases we consider the balance of both relevant parts of the employment history and academic qualifications.
English language requirements: IELTS 6.5 (with 6 in each component) or University equivalent.
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:
How to get a full scholarship
Looking for a fully-funded scholarship to see you into university? Find out how to boost your chances of getting one.
Scholarships to study abroad
Find scholarships to study abroad with our lists of international scholarships – categorized by country, by subject, and by type of student.
Scholarship Applications: Frequently Asked Questions
Get answers to all your questions about scholarship applications, including tips on how to find scholarships and chances of success.
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