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Book Summary:
Model formulae represent a powerful methodology for describing, discussing, understanding, and performing that large part of statistical tests known as linear statistics. It was developed for professional statisticians in the 1960s, and has become increasingly available to the statistically aware and literate as computers have grown and software has advanced. The book puts this methodology firmly within the grasp of undergraduates for the first time. It provides the conceptual framework needed to understand what the method does, but without mathematical proofs. It introduces 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 ask advice from professional statisticians, 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, a key advantage is that 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 puts within the reach of undergraduates and graduates the statistical analyses their projects and practicals really require. |
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