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  • Research resources

    The University of Leicester holds excellent research resources for medieval studies, such as the significant collection of manuscripts and rare books held in the University Library. Find out more about these available resources.

  • Advanced Statistical Modelling (Part-time)

    Module code: MD7468 Generalised linear models This module will start by introducing the theory of generalized linear models (GLMs) in terms of exponential family of distributions and discussing special cases of GLMs, such as normal, Poisson or binomial regression.

  • Writing for Laughs

    Module code: EN3204 This module aims to mix creative writing, criticism and theory in its exploration of modern and contemporary comedy.

  • Advanced Statistical Modelling (Part-time)

    Module code: MD7468 Generalised linear models This module will start by introducing the theory of generalized linear models (GLMs) in terms of exponential family of distributions and discussing special cases of GLMs, such as normal, Poisson or binomial regression.

  • Costs and what's included

    Information about fees for our undergraduate accommodation, including details of all-inclusive rent and prepayment.

  • University lecture focuses on 1994 genocide against the Tutsi community

    The long term effects of rape on women survivors of the 1994 genocide against the Tutsi community will be discussed at a lecture at our University.

  • Dutch

    Study Dutch courses for all levels at The University of Leicester.

  • Writing for Laughs

    Module code: EN3204 This module aims to mix creative writing, criticism and theory in its exploration of modern and contemporary comedy.

  • Citizens of Change

    Discover the benefits of studying here at Leicester by ordering either an undergraduate or postgraduate prospectus.

  • Advanced Statistical Modelling (Part-time)

    Module code: MD7468 Generalised linear models This module will start by introducing the theory of generalized linear models (GLMs) in terms of exponential family of distributions and discussing special cases of GLMs, such as normal, Poisson or binomial regression.

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