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Modern Statistics for the Life Sciences | |||||
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Rok: 2002
Hodnocení: AnotaceModel formulae represent a powerful methodology for describing, discussing, understanding, and performing the component of statistical tests known as linear statistics. It was developed for professional statisticians in the 1960s and has become increasingly available as the use of computers has grown and software has advanced. Modern Statistics for Life Scientists puts this methodology firmly within the grasp of undergraduates for the first time. The authors assume a basic knowledge of statistics--up to and including one and two sample t-tests and their non-parametric equivalents. They provide the conceptual framework needed to understand what the method does--but without mathematical proofs--and introduce the ideas in a simple and steady progression with worked examples and exercises at every stage. Students learn a single conceptual framework for a wide range of tests often introduced separately, including t-tests, oneway and multiway analysis of variance, linear and polynomial regressions, and analysis of covariance. More importantly, students learn a language in which they can frame questions and in which they also communicate with the computer that performs the analyses. All the examples and exercises are available in separate online documents in Minitab, SAS and SPSS. For students who go on to research, model formulae in linear models are the best springboard from which to reach an understanding of more advanced methods such as logistic regression and log-linear models. This book is appropriate for use in statistics courses at undergraduate and graduate levels. It is also a helpful resource for students of non-mathematics-based disciplines using statistics, such as Geography, Psychology, and Epidemiology, as well as for postgraduate researchers in the Life Sciences. Dostupné zdroje
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