University of Manchester Campus
Bachelor of Science
On Campus
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University of Manchester
Manchester
United Kingdom

Mathematics and Statistics

About

The Bachelor of Science in Mathematics and Statistics at the University of Manchester is a three-year, full-time program designed for students with a strong interest in both the theoretical and practical applications of mathematics and statistics. This program offers a solid foundation in mathematical principles, combined with a thorough understanding of statistical methods and their use in analyzing data. Mathematics and statistics are critical in a wide range of fields, from finance and engineering to medicine and social sciences, and this program prepares students for careers that require advanced analytical and problem-solving skills.

Throughout the program, students will study a variety of topics, including calculus, algebra, probability theory, statistical inference, and data analysis. The program emphasizes the application of mathematical and statistical models to real-world problems, providing students with the tools needed to analyze complex data sets and make informed decisions. Students will also have the opportunity to engage in project work, which encourages them to apply their knowledge in practical settings. Graduates will be well-equipped to pursue careers in data science, finance, research, operations research, or any other field that requires strong quantitative skills. With a solid grounding in mathematics and statistics, students will also be prepared for postgraduate study in related areas.

Key information

Duration
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Tuition fee
$48,457.00/year
Start dates & application deadlines
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More details
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Key Facts

  • Program Title: Bachelor of Science (BSc) in Mathematics and Statistics
  • Degree Type: Bachelor of Science (BSc)
  • Duration: 3 years
  • Mode of Study: Full-time, On Campus
  • Application Deadline: 14th January 2026
  • Location: University of Manchester, United Kingdom
  • Field of Study: Mathematics
  • Language of Instruction: English

Program Structure

Year 1 – Foundations of Mathematics and Statistics

  • Introduction to Calculus and Algebra
  • Probability and Statistics
  • Mathematical Proofs and Logic
  • Linear Algebra and Matrix Theory
  • Introduction to Programming and Computational Methods

Year 2 – Intermediate Mathematics and Statistical Methods

  • Multivariable Calculus and Differential Equations
  • Statistical Inference and Regression Analysis
  • Real Analysis and Complex Variables
  • Stochastic Processes and Time Series Analysis
  • Data Science and Computational Statistics

Year 3 – Advanced Mathematics and Statistics

  • Advanced Topics in Probability Theory
  • Statistical Modelling and Machine Learning
  • Optimization Techniques and Mathematical Modelling
  • Applied Statistics and Research Methods
  • Final Year Research Project/Dissertation

Career Opportunities

Graduates of the Mathematics and Statistics program are well-prepared for careers in data science, financial analysis, statistical research, and academia. Career opportunities include roles such as data analyst, statistician, actuary, financial analyst, and research scientist. Graduates can work in sectors such as finance, healthcare, government agencies, technology companies, and research institutions. The strong foundation in both mathematics and statistics prepares students for high-demand roles in industries requiring complex problem-solving and data analysis skills.

Why Choose This Program

The Mathematics and Statistics program at the University of Manchester offers a rigorous education in both theoretical and applied mathematics, combined with a strong emphasis on statistical analysis. Students will develop a deep understanding of mathematical principles, alongside advanced skills in data analysis, statistical modelling, and computational techniques. This program is ideal for those looking to pursue careers in data science, finance, or research, providing a solid foundation for further study or professional practice in mathematics, statistics, and related fields.