When the Distribution Is Known

Phillip I. Good ()

Chapter Chapter 4 in Resampling Methods, 2001, pp 60-71 from Springer

Abstract: Abstract One of the strengths of the hypothesis-testing procedures described in the preceding chapter is that you need to know very little about the underlying population(s) to apply them. But suppose you have full knowledge of the processes that led to the observations in your sample(s), should you still use the same statistical tests? The answer is no, not always, particularly with very small or very large amounts of data. In this chapter, we consider several parameter-based distributions including the binomial (which you were introduced to in Chapter 2), the Poisson, and the normal or Gaussian, along with several other parametric distributions derived from them that are of value in testing location and dispersion.

Keywords: Poisson Distribution; Binomial Distribution; Independent Observation; Independent Trial; Orange County (search for similar items in EconPapers)
Date: 2001
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Persistent link: https://EconPapers.repec.org/RePEc:spr:sprchp:978-1-4757-3425-6_4

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DOI: 10.1007/978-1-4757-3425-6_4

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