This book goes beyond specific methods in specific applications to consider the full range of techniques which can be used to solve a statistical problem. This applied text treats general topics such as one- and two-sample problems, one- and two-way classifications, regression analysis, ratios and variances. It includes helpful problem-solving hints and references along with theoretical and real-life exercises at the end of each chapter.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
Renowned statistician R.G. Miller set the pace for statistics students with Beyond ANOVA: Basics of Applied Statistics. Designed to show students how to work with a set of "real world data," Miller's text goes beyond any specific discipline, and considers a whole variety of techniques from ANOVA to empirical Bayes methods; the jackknife, bootstrap methods; and the James-Stein estimator.
This reissue of Miller's classic book has been revised by professors at Stanford University, California. As before, one of the main strengths of Beyond ANOVA is its promotion of the use of the most straightforward data analysis methods-giving students a viable option, instead of resorting to complicated and unnecessary tests.
Assuming a basic background in statistics, Beyond ANOVA is written for undergraduates and graduate statistics students. Its approach will also be valued by biologists, social scientists, engineers, and anyone who may wish to handle their own data analysis.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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