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9: Hypothesis Testing

Last updated

May 5, 2020
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- 8.5: Bayesian Set Estimation
- 9.1: Introduction to Hypothesis Testing

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Hypothesis testing refers to the process of choosing between competing hypotheses about a probability distribution, based on observed data from the distribution. It is a core topic in mathematical statistics, and indeed is a fundamental part of the language of statistics. In this chapter, we study the basics of hypothesis testing, and explore hypothesis tests in some of the most important parametric models: the normal model and the Bernoulli model.

9.1: Introduction to Hypothesis Testing
In hypothesis testing, the goal is to see if there is sufficient statistical evidence to reject a presumed null hypothesis in favor of a conjectured alternative hypothesis.
9.2: Tests in the Normal Model
9.3: Tests in the Bernoulli Model
9.4: Tests in the Two-Sample Normal Model
9.5: Likelihood Ratio Tests
9.6: Chi-Square Tests

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