Abstract
A parameter can be estimated from sample data either by a single number (a point estimate) or an entire interval of plausible values (a confidence interval). Frequently, however, the objective of an investigation is not to estimate a parameter but to decide which of two contradictory claims about the parameter is correct. Methods for accomplishing this comprise the part of statistical inference called hypothesis testing. In this chapter, we first discuss some of the basic concepts and terminology in hypothesis testing and then develop decision procedures for the most frequently encountered testing problems based on a sample from a single population.
Keywords
- Rejection Region
- Upper-tailed Test
- Perfluorooctanoic Acid (PFOA)
- Normal Population Distribution
- Neyman-Pearson Theorem
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.
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© 2012 Springer Science+Business Media, LLC
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Devore, J.L., Berk, K.N. (2012). Tests of Hypotheses Based on a Single Sample. In: Modern Mathematical Statistics with Applications. Springer Texts in Statistics. Springer, New York, NY. https://doi.org/10.1007/978-1-4614-0391-3_9
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DOI: https://doi.org/10.1007/978-1-4614-0391-3_9
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Publisher Name: Springer, New York, NY
Print ISBN: 978-1-4614-0390-6
Online ISBN: 978-1-4614-0391-3
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