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Mathematics & Statistics BSc

Study of mathematical theory, probability, and data to understand patterns and make predictions.

YOUR PERSONALITY MIGHT BE:

Analytical thinker

Detail-oriented

Logical problem-solver

Patient and methodical

POPULAR CAREER FIELDS

Finance & Banking

Research & Academia

Government & Public Sector

Consulting

Is this for you?

Mathematics & Statistics BSc

Is this for you?

WHAT IS IT?

Study of mathematical theory, probability, and data to understand patterns and make predictions.

CAREER OPTIONS

CURRENT APPRENTICESHIPS, INTERNSHIPS & WORKPLACES

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About the Course

  • What Is a Mathematics & Statistics Degree?

    Mathematics & Statistics combines pure and applied maths with data analysis and probability. It focuses on how to model uncertainty, interpret data, and draw conclusions that inform real-world decisions in science, business, and society.


    Why Study Mathematics & Statistics?

    From predicting weather and disease to analysing financial markets, statistics and mathematics are everywhere. This degree gives you the logical reasoning and technical skills to turn data into insight, preparing you for careers in research, technology, and analytics.

  • Most Mathematics & Statistics degrees cover:


    • Calculus, algebra, and linear mathematics

    • Probability theory and stochastic processes

    • Statistical inference and modelling

    • Data analysis and visualisation

    • Programming for statistics (often in R, Python, or MATLAB)

    • Mathematical modelling and optimisation

    • Applied statistics in science, business, or economics


    Later in your course, you can usually specialise, for example, in actuarial mathematics, data science, epidemiology, or financial statistics.



    Degree Types

    • BSc (Bachelor of Science): Focuses on the analytical, applied, and computational side of maths and statistics.

    • MSci or Integrated Master’s: A four-year degree for advanced study and research experience.

  • Statistical Modelling – building and analysing models using probability, inference, and regression techniques.


    Advanced Mathematical Reasoning – applying algebra, calculus, and logic to complex quantitative problems.


    Data Analysis – interpreting datasets using statistical tests, estimations, and computational tools.


    Programming for Statistics – using languages like R, Python, or MATLAB for data and statistical work.


    Problem-Solving – applying mathematical and statistical methods to real-world decision-making and research.

  • A-levels or equivalent including Maths. Further Maths is highly beneficial and often recommended. Physics, Economics, or Computer Science are also beneficial.


    • Show your interest in both mathematics and statistics.

    • Mention any projects, competitions, or courses involving data or problem-solving.

    • Reflect on how you enjoy finding patterns and meaning in numbers.

    • Include independent learning, such as online courses or data challenges.

    • The Art of Statistics by David Spiegelhalter – A clear guide to making sense of data.

    • The Signal and the Noise by Nate Silver – How statistical thinking helps make better predictions.

    • How Not to Be Wrong: The Power of Mathematical Thinking by Jordan Ellenberg – How maths explains everyday life.

    • The Drunkard’s Walk by Leonard Mlodinow – An engaging look at probability and randomness.

    • Compare courses to see the balance between maths, statistics, and computing.

    • Attend open days or online sessions to meet lecturers and explore facilities.

    • Try online tutorials in probability, R, or Python.

    • Read about how maths and statistics are used in science, business, and policy.

    • Statistics - Statistician, senior statistician, principal statistician

    • Data Science - Data scientist, statistical data scientist, analytics scientist

    • Quantitative Finance - Quantitative analyst, statistical modeler, risk analyst

    • Government Statistics - Government statistician, ONS statistician, public sector analyst

    • Biostatistics - Biostatistician, medical statistician, clinical trials statistician

    • Data Analysis - Data analyst, statistical analyst, analytics manager

    • Research - Statistical researcher, academic researcher, survey researcher

    • Risk Analysis - Risk analyst, actuarial analyst, statistical risk modeler

    • Market Research - Market research analyst, consumer insights analyst, survey analyst

    • Clinical Trials - Clinical trials statistician, pharmaceutical statistician, medical data analyst

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