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  • Statistics for Data Science

    Module code: MA7023 The most important method in statistical analysis is the natural extension of simple linear regression models to include several explanatory variables, thus giving general linear models.

  • Statistics for Data Science

    Module code: MA7023 The most important method in statistical analysis is the natural extension of simple linear regression models to include several explanatory variables, thus giving general linear models.

  • Learn to speak Student

    A university is a self-contained little world with its own language and jargon, which you will pick up during your time here. Use this page to get up to speed with some of the essentials.

  • Statistics for Data Science

    Module code: MA7023 The most important method in statistical analysis is the natural extension of simple linear regression models to include several explanatory variables, thus giving general linear models.

  • Introduction to Management

    Module code: MN1033 This module explores the issues of planning, organising, leading, and controlling within contemporary organisations.  You will examine how managers coordinate resources to achieve strategic objectives.

  • Introduction to Management

    Module code: MN1033 This module explores the issues of planning, organising, leading, and controlling within contemporary organisations.  You will examine how managers coordinate resources to achieve strategic objectives.

  • Introduction to Management

    Module code: MN1033 This module explores the issues of planning, organising, leading, and controlling within contemporary organisations.  You will examine how managers coordinate resources to achieve strategic objectives.

  • Meet the team

    Learn more about the team of Chaplains working at the University of Leicester and how you can get in touch with them.

  • Epidemiology for Health Data Science

    Module code: MD7474 Modelling in epidemiology project The project is designed to give you experience in analysing epidemiological data using logistic and Poisson models. The project uses real datasets, which inevitably comes with some real problems.

  • Work experience and industry links

    Through our links with industry, Geology has a large number of students who undertake work experience during their vacations, or through a year out in industry. Such work experience gives our students a strong competitive edge in securing permanent employment.

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