Overview
Statistics and probability are the cornerstones of modern data science, machine learning, and artificial intelligence. As these skills become increasingly important across various fields, our Statistics MSc programme will equip you with the knowledge and expertise needed for your career.
Through this degree, you’ll embark on your journey to master statistics. Take your understanding to new depths, while challenging yourself with finding data-driven solutions to real-world problems.
This Statistics MSc offers a unique blend of graduate training in statistics and probability, as well as their practical application. You’ll explore a wide range of advanced topics and will gain a comprehensive understanding of the discipline. Our curriculum is designed to develop your expertise in cutting-edge research, allowing you to foster innovation and stay at the forefront of your chosen field.
A key feature of this programme is the dissertation project. You’ll bridge the gap between academic theory and real-world application. You’ll work directly with both industry leaders and our esteemed academics who are pioneers in their discipline. Through this hands-on experience, you will:
- tackle real challenges faced by companies and researchers
- build a professional network
- gain invaluable experience that will set you apart in your career
READ LESS
Important information
We’ve highlighted important information about your course. Please take note of any deadlines.
Your course and study experience – disclaimers and terms and conditions
Please rest assured we make all reasonable efforts to provide you with the programmes, services and facilities described. However, it may be necessary to make changes due to significant disruption, for example in response to Covid-19.
View our Academic experience page, which gives information about your Newcastle University study experience for the academic year 2024-25.
See our terms and conditions and student complaints information, which gives details of circumstances that may lead to changes to programmes, modules or University services.
Qualifications explained
Find out about the different qualification options for this course.
MSc – Master of Science
An MSc is a taught Master’s degree. It usually involves the study of a science-related subject.
You’ll usually study an MSc full-time over 12 months.
A Master of Science is typically awarded for the successful completion of 100 credits of taught modules and an 80-credit dissertation or research project.
Find out about different types of postgraduate qualifications.
What you’ll learn
You’ll develop an understanding of fundamental statistics and probability, while gaining practical skills in data management, integration, and handling. You’ll also gain expertise in a broad range of computational and statistical methods for solving complex data analysis problems.
Exposure to various application areas and the choice of specialisms for in-depth study will further enhance your learning experience.
Your dissertation project will position you as a well-rounded expert, ready to contribute meaningfully to any organisation or research institution.
Modules
You will study modules on this course. A module is a unit of a course with its own approved aims and outcomes and assessment methods.
Course content changes
Module information is intended to provide an example of what you will study.
Our teaching is informed by research. Course content changes periodically to reflect developments in the discipline, the requirements of external bodies and partners, and student feedback.
Full details of the modules on offer will be published through the Programme Regulations and Specifications ahead of each academic year. This usually happens in May.
To find out more please see our terms and conditions.
Optional modules availability
Some courses have optional modules. Student demand for optional modules may affect availability.
Compulsory modules
- Graduate Foundations of Statistics and Data Science (30 credits)
- Graduate Foundations of Probability and Mathematical Statistics (30 credits)
You must choose one of the following modules:
- Dissertation in Statistics (60 credits)
- Industrial Dissertation in Statistics and Data Science (60 credits)
Optional modules
You must choose 60 credits from the following list of optional modules:
- Clinical Trials with Advanced Topics (10 credits)
- Decision Modelling for Health Data Science with Advanced Topics (10 credits)
- Advanced Topics in Medical Statistics and Health Data Science (10 credits)
- Statistical Foundations of Machine Learning with Advanced Topics (10 credits)
- Experimental Design with Advanced Topics (10 credits)
- Probability Theory with Advanced Topics (10 credits)
- Extreme Value Theory with Advanced Topics (10 credits)
- Sports Modelling with Advanced Topics (10 credits)
- Survival Analysis with Advanced Topics (10 credits)
- Time Series with Advanced Topics (10 credits)
- Stochastic Financial Modelling with Advanced Topics (10 credits)
- Statistical Genetics with Advanced Topics (10 credits)
- Advanced Topics in Statistics and Data Science (10 credits)
How you’ll learn
You’ll be taught using a range of methods, including:
- lectures
- seminars
- practical computer lab sessions
- group work
- project work
Teaching will be delivered by experts from the School of Mathematics, Statistics, and Physics.
Depending on your modules, you’ll be assessed through a combination of:
- Case study
- Computer assessment
- Dissertation
- Oral presentation
- Poster
- Problem-solving exercises
- Report
- Written examination
- Written exercise
Numbas learning software
You’ll have access to a specialist learning software called Numbas. Developed at Newcastle University, it’s now used by mathematicians and statisticians worldwide.
This innovative software allows you to work on interactive code worksheets, so you can test and refine your skills throughout your course.
Specialist software and tool support
You’ll have support from our award-winning Digital Learning Team, who can assist you with the specialised software and tools you need for the programme.
Your teaching and learning is also supported by Canvas. Canvas is a Virtual Learning Environment. You’ll use Canvas to submit your assignments and access your:
- module handbooks
- course materials
- groups
- course announcements and notifications
- written feedback
Throughout your studies, you’ll have access to support from:
- peers
- academics
- personal tutors
- our University Student Services Team
- student representatives
You’ll also be assigned an academic member of staff. They will be your personal tutor throughout your time with us. They can help with academic and personal issues.
This course is delivered by the School of Mathematics, Statistics and Physics. Our teaching staff are experts working at the forefront of statistical research and practice.
You’ll work alongside academics from the following research groups:
- Statistics: World-class research in modern statistics and data science.
- Astrostatistics: Cutting-edge research being carried out at the interface of physics and statistics, using modern data science techniques to help understand the universe.
- Scalable Computing: Internationally renowned for tackling research challenges in high performance systems, data science, machine learning and data visualisation.
- Biostatistics: Over 30 statisticians working in developing and applying innovative methods in clinical trials and observational studies.
Newcastle University is also home to the UK’s National Innovation Centre for Data (NICD), which has extensive links with industrial partners across a range of sectors.
Your development
You’ll develop your essential skills and experience throughout your course.
You’ll learn professional skills needed for your career including critical thinking, problem-solving, and communicating complex insights. You’ll also master research skills through an extended dissertation project. You’ll use advanced statistical theory and apply computational tools to real-world problems.
You’ll also develop practical skills in data storage, manipulation, and presentation using statistical software, along with the ability to effectively communicate insights.
Your future
Your career
Through our strong industry connections, fostered by both our research and degree programme, you’ll gain valuable insights and opportunities to explore diverse career paths.
Our Statistics MSc prepares you for a wide range of careers involving statistics and data science, fundamental in areas such as:
- AI development
- finance
- consultancy
- healthcare
- research
You could pursue a career in roles such as:
- Data Scientist
- Statistician
- Biostatistician
- Data Analyst
- Risk Analyst
- Machine Learning Engineer
Further study
This course provides a route into PhD level study in various fields, depending on your choice of optional modules. Examples include:
- statistical methodology
- probability theory
- applied statistical science
Our Careers Service
Our award-winning Careers Service is one of the largest and best in the country, and we have strong links with employers. We provide an extensive range of opportunities to all students through our ncl+ initiative.
Quality and ranking
- 42% of our research is classified as 4* world-leading research – Research Excellence Framework 2021
- 65% increase in research power since 2014 – Research Excellence Framework 2021
- Global Top 130 University – QS World University Rankings 2025
- Global Top 170 University – Times Higher Education World University Rankings 2024
- Top 200 for Statistics and Operational Research – QS World University Rankings by Subject 2024
- Top 25 in the UK and Top 100 in the world for sustainable development – Times Higher Education Impact Rankings 2024
Recognition of professional qualifications outside of the UK
From 1 January 2021 there is an update to the way professional qualifications are recognised by countries outside of the UK
Facilities
You’ll have access to our facilities in the School of Mathematics, Statistics, and Physics, including our computer cluster and new Learning Lab.
Collaborations with the National Innovation Centre for Data (NICD) and other industry partners will also enhance your learning experience.
Entry requirements
The entrance requirements below apply to 2025 entry.
Academic entry requirements
A 2:1 BSc honours degree, or international equivalent, in mathematical sciences or another quantitative degree with a formal mathematical component. Examples include, but are not limited to, computer sciences, economics, engineering and similar disciplines.
Applicants from a non-standard background and individuals with strong relevant work experience are encouraged to apply and will be considered on an individual basis.
