Statistical Science (Distance Learning) MSc
Program start date | Application deadline |
2025-09-01 | - |
Program Overview
Statistical Science (Distance Learning) MSc
Overview
The Statistical Science MSc is a part-time distance learning programme, offering you the flexibility to study your way. You will develop the advanced techniques and skills required to be a successful statistician in the 21st century.
Course Details
- Duration: 24-72 months (part-time)
- Start Date: September 2025
- UK Fees: £12,410
- International Fees: £12,410
- Entry Requirements: A high 2:2 (greater than 55% or international equivalent) in mathematics or a closely related subject with substantial mathematical content.
Course Content
Year 1
- Foundations of Statistics (20 credits)
- Frequentist Statistical Inference (20 credits)
- Statistical Modelling of Discrete and Survival Data (20 credits)
- Bayesian Data Analysis: Theory, Applications and Computational Methods (20 credits)
- Statistical Machine Learning (20 credits)
- Multivariate and Time Series Analysis (20 credits)
Year 2
- Statistics Dissertation (60 credits)
Learning and Assessment
- How you will learn: Independent study, distance learning materials, lectures, eLearning
- How you will be assessed: Examinations, coursework, dissertation, short project
Entry Requirements
- Undergraduate degree: A high 2:2 (greater than 55% or international equivalent) in mathematics or a closely related subject with substantial mathematical content.
- Portfolio: Some prior knowledge of statistics would be helpful but not essential to start the course.
- Familiarity with: The basics of calculus (differentiation and integration) and linear algebra (matrices and vectors) is assumed.
- English language requirements: IELTS 6.5 (6.0 in each element.)
Funding
- Scholarships: We offer a range of international masters scholarships for high-achieving international scholars who can put their Nottingham degree to great use in their careers.
- Government loans: Available for eligible students.
Careers
- Careers advice: We offer individual careers support for all postgraduate students.
- Job prospects: Graduates go on to a wide range of careers, including banking, education, finance, healthcare, sport, and transport.
- Career progression: 96% of postgraduates from the School of Mathematical Sciences secured graduate level employment or further study within 15 months of graduation.
Related Courses
- Statistics MSc
- Statistics with Machine Learning MSc
- Machine Learning in Science MSc
Program Outline
Degree Overview:
The Statistical Science MSc is a part-time distance learning program designed to provide flexibility for students. The program aims to equip students with advanced statistical techniques and skills to become successful statisticians in the 21st century. As the demand for analysts who can interpret and analyze data increases, the MSc ensures students gain the skills to explore, model, analyze, and present data effectively.
Outline:
The program consists of 120 credits of taught modules over three semesters, with a dissertation in the final semester.
Year 1
- Semester 1: Foundations of Statistics, Frequentist Statistical Inference
- Semester 2: Statistical Modelling of Discrete and Survival Data, Bayesian Data Analysis: Theory, Applications and Computational Methods
Year 2
- Semester 1: Statistical Machine Learning, Multivariate and Time Series Analysis
Dissertation
- 60 credit dissertation to be completed after taught component during February - September in Year 2.
Assessment:
- Examinations
- Coursework
- Dissertation
- Short project Exams will take place at the university or an approved test center at the end of each semester. Students must achieve a weighted average mark of at least 50% with no more than 40 credits below 50% and no more than 20 credits below 40%. A mark of at least 50% must be achieved in the dissertation.
Teaching:
Teaching is provided through course materials including lecture notes, digital recordings, training videos, and practical computer sessions. Students have the flexibility to access these materials in their own time. Live online sessions using Microsoft Teams (or similar) provide opportunities for students to ask questions and interact with lecturers.
Careers:
Graduates will develop valuable skills in logical thinking, problem-solving, data analysis and manipulation, and communicating statistical findings. They can pursue careers in various fields, including banking, education, finance, healthcare, sport, and transport. The MSc also opens up opportunities in data science.
Other:
- The program is supported by expert lecturers and leading statistical experts and researchers.
- The school was placed in the top 3 for quality of research environment across all mathematical sciences units in the UK.
- 100% of the impact from the school is rated as either ‘world-leading’ or ‘internationally excellent’.
If you are a student from the EU, EEA or Switzerland, you may be asked to complete a fee status questionnaire and your answers will be assessed using . These fees are for full-time study. If you are studying part-time, you will be charged a proportion of this fee each year (subject to inflation).
Additional costs
- Books: Non-essential (materials complete) but might be helpful. A wide range of statistics books can be accessed electronically through the library.
- Equipment: A computer is essential to access the learning materials, use statistical software and prepare reports for assignments. A laptop is preferable.
- Travel: Travel will be required to attend the University of Nottingham or an approved test centre for examinations.
- Assessment costs: There will be additional assessment costs if examinations are taken at a venue other than a University of Nottingham campus. The costs will be venue specific.
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Entry Requirements:
Home / UK students:
- A high 2:2 in mathematics or a closely related subject with substantial mathematical content.
EU / International students:
- A high 2:2 (or international equivalent) in mathematics or a closely related subject with substantial mathematical content.
Portfolio:
- Some prior knowledge of statistics would be helpful but not essential to start the course.
- Familiarity with the basics of calculus (differentiation and integration) is assumed.
Language Proficiency Requirements:
- IELTS 6.5 (6.0 in each element.)