Mathematical Statistics 245 (MS245)

Stellenbosch University (SUN)

Here are the best resources to pass Mathematical Statistics 245 (MS245). Find Mathematical Statistics 245 (MS245) study guides, notes, assignments, and much more.

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Intro to probability distributions Intro to probability distributions
  • Intro to probability distributions

  • Summary • 8 pages • 2023
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  • An intro to concepts relating to probability distributions.
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Intro to probability distributions and related concepts Intro to probability distributions and related concepts
  • Intro to probability distributions and related concepts

  • Summary • 6 pages • 2023
  • Available in package deal
  • This material covers introductory statistical concepts, such as bivariate distributions and moment-generating functions.
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Summary and Examples Mathematical Statistics with Applications, ISBN: 9781111798789  Mathematical Statistics 245 (MS245) Summary and Examples Mathematical Statistics with Applications, ISBN: 9781111798789  Mathematical Statistics 245 (MS245)
  • Summary and Examples Mathematical Statistics with Applications, ISBN: 9781111798789 Mathematical Statistics 245 (MS245)

  • Summary • 64 pages • 2020
  • Available in package deal
  • This document contains a brief summary and many examples of point estimators, order statistics, relative efficiency, method of moment estimators, method of maximum likelihood estimators, Neyman-Pearson Lemma, likelihood ratio test, Bayesian statistics (conjugate priors, noninformative priors, credibility intervals, squared error loss functions, absolute error loss functions, etc.).
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Summary Mathematical Statistics with Applications, ISBN: 9781111798789  Mathematical Statistics 245 (MS245) Summary Mathematical Statistics with Applications, ISBN: 9781111798789  Mathematical Statistics 245 (MS245)
  • Summary Mathematical Statistics with Applications, ISBN: 9781111798789 Mathematical Statistics 245 (MS245)

  • Summary • 51 pages • 2020
  • Available in package deal
  • This document contains comprehensive summaries of point estimators, order statistics, relative efficiency, method of moment estimators, method of maximum likelihood estimators, Neyman-Pearson Lemma, likelihood ratio test, Bayesian statistics (conjugate priors, noninformative priors, credibility intervals, squared error loss functions, absolute error loss functions, etc.). This document also contains a brief summary of general hypothesis tests and p-values.
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