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Statistical Hypothesis Testing with SAS and R by Dirk Taeger, Sonja Kuhnt

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Preface

Statistical hypothesis testing has been introduced almost one hundred years ago and has become a key tool in statistical inferences. The number of available tests has grown rapidly over the decades. With this book we present an overview of common statistical tests and how to apply them in SAS and R. For each test a general description is provided as well as necessary prerequisites, assumptions and the formal test problem. The test statistic is stated together with annotations on its distribution. Additionally two examples, one in SAS and one in R, are given. Each example contains the code to perform the test using a tiny dataset, along with output and remarks that explain necessary program parameters.

This book is addressed to you, whether you are an undergraduate student who must do course work, a postgraduate student who works on a thesis, an academic or simply a practitioner. We hope that the clear structure of our presentation of tests will enable you to perform statistical tests much faster and more directly, instead of searching through documentation or looking on the World Wide Web. Hence, the book may serve as a reference work for the beginner as well as someone with more advanced knowledge or even a specialist.

The book is organized as follows. In the first part we give a short introduction to the theory of statistical hypothesis testing and describe the programming philosophy of SAS and R. This part also contains an example of how to perform statistical tests ...

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