This certificate teaches the theory that underpins statistical inference and probability. Equipping you to understand the assumptions and limitations of a range of statistical models. You’ll gain a thorough understanding of the theory you need to underpin your work as a professional statistician. Learn to develop probability models for practical situations and investigate the model’s properties. Study the mathematical theory underlying methods and concepts used in practical statistical analyses. **Key features of the course** - Cover key analytical approaches, classical and Bayesian statistics and the underpinning mathematical theory. - Learn about distribution theory and a range of probabilistic models. - Understand the theory behind statistical inference. - Gain the skills to critically comment on analyses and model choices.

This certificate has one stage, comprising 60 credits. You’ll start Stage 1 with either 30-credit module or take both together.

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Institution code: O11

Campus Name: Distance Learning

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The following entry points are available for this course:

Year 1

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You must have an undergraduate degree with a substantial amount of mathematical and/or statistical content. You need a high degree of mathematical competence in the following areas: logarithmic and exponential functions calculus (including Taylor series) algebra (including manipulation of inequalities) matrices In addition, you’ll need a working knowledge of the following statistical topics: histograms and scatterplots normal, Poisson and binomial distributions the central limit theorem point estimation maximum likelihood estimation confidence intervals hypothesis testing simple linear regression correlation

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Milton Keynes
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