Mathematical Statistics 245 (MS245)
Stellenbosch University (SUN)
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Mathematical Statistics with Applications
Dennis Wackerly, William Mendenhall, Richard L. Scheaffer
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Probability theory and statistics class notes and summaries
- Package deal • 3 items • 2024
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The class notes cover important concepts for anyone starting off in statistics. They cover the fundamentals of probability theory as well as an introduction to probability distributions and statistics. Includes summaries for various probability distributions that are commonly used throughout statistical studies.
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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
- Summary • 6 pages • 2023
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This material covers introductory statistical concepts, such as bivariate distributions and moment-generating functions.
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Mathematical Statistics 245 Summaries and Examples Bundle
- Package deal • 2 items • 2020
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- R175,00
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A combination of comprehensive summaries and 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
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Summary and Examples Mathematical Statistics with Applications, ISBN: 9781111798789 Mathematical Statistics 245 (MS245)
- Summary • 64 pages • 2020
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- R130,00
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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 • 51 pages • 2020
- Available in package deal
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- R130,00
- 1x sold
- + learn more
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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