Titlebook: Exact Statistical Methods for Data Analysis; Samaradasa Weerahandi Book 1995 Springer Science+Business Media New York 1995 data analysis.a

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https://doi.org/10.1007/978-1-4613-1305-2ide formulae for computing exact p-values even for testing parameters of special distributions. The purpose of this chapter is to develop procedures of significance testing for the parameters of widely used distributions, such as the binomial distribution. The problems of point estimation and interv

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Kathy Charles,Michael Palkowskitributions from which the observations are taken, and then make inferences about some of its unspecified parameters. In particular, the linear models in the last three chapters of the book are all based on the assumption that the underlying populations are normally distributed. While this assumption

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https://doi.org/10.1007/978-3-319-50553-4ous problems involving parameters of two normal populations. Statistical inferences concerning the parameters of two normal distributions arise in the comparison of two treatments, brands, market segments, services, etc. Experimenters in a variety of fields including biomedical research, agricultura

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Feeding Occupied France during World War Ire than two normal populations. In practical applications, often we need to compare several population means. For example, an investigator might wish to compare several brands of a product, or diet plans, or methods of instruction, or advertising methods, and so on. When samples are taken from under

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Survival Strategies of Meiofauna, of levels. This is indeed the case in many designed experiments. In other designed experiments, and in many other situations, we encounter response variables that depend linearly on one or more continuous variables. Both of these are particular cases of what is known as . The purpose of this chapte