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This fifth edition of a classic text is appropriate for a one semester general course in Applied Statistics or as a reference book for practicing researchers in a wide variety of disciplines, including medicine, health and human services, natural and social sciences, law, and engineering. This practical book describes the Bayesian principles necessary for applied clinical research and strategic interaction, which are frequently omitted in other texts. After a comprehensive treatment of probability theory concepts, theorems, and some basic proofs, this concisely written text illustrates sampling distributions and their importance in estimation for the purpose of statistical inference. The book then shifts its focus to the essentials associated with confidence intervals and hypothesis testing for major population parameters; namely, the population mean, population variance, and population proportion. In addition, it thoroughly describes the properties of expectations and variance, the basics of correlation and simple linear regression, as well as non-parametric statistics.
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This fifth edition of a classic text is appropriate for a one semester general course in Applied Statistics or as a reference book for practicing researchers in a wide variety of disciplines, including medicine, health and human services, natural and social sciences, law, and engineering. This practical book describes the Bayesian principles necessary for applied clinical research and strategic interaction, which are frequently omitted in other texts. After a comprehensive treatment of probability theory concepts, theorems, and some basic proofs, this concisely written text illustrates sampling distributions and their importance in estimation for the purpose of statistical inference. The book then shifts its focus to the essentials associated with confidence intervals and hypothesis testing for major population parameters; namely, the population mean, population variance, and population proportion. In addition, it thoroughly describes the properties of expectations and variance, the basics of correlation and simple linear regression, as well as non-parametric statistics.
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