This is a history of parametric statistical inference, written by one of the most important historians of statistics of the ...
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Most data sets collected by researchers are multivariate, and in the majority of cases the variables need to be examined ...
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Analysis of variance (ANOVA) models have become widely used tools and play a fundamental role in much of the application ...
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This book presents a step-by-step manner that eliminates the greatest obstacle to the learner, which is applying the many ...
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Geometric Data Analysis (GDA) is the name suggested by Stanford University to designate the approach to Multivariate Statistics ...
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R is an Open Source implementation of the S language. It works on multiple computing platforms and can be freely downloaded. ...
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This book teaches the art and statistical science of modern longitudinal data analysis. The author emphasizes specifying, ...
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This second edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean ...
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PROCESS OPTIMIZATION: A Statistical Approach is a textbook for a course in experimental optimization techniques for industrial ...
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This book explains in detail, with supporting examples, one of the most common statistical methods: regression. The first ...
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This book is an integrated treatment of applied statistical methods, presented at an intermediate level, and the SAS programming ...
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This book brings together accounts by leading international experts that are essential reading for those working in fields ...
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Although statistical design is one of the oldest branches of statistics, its importance is ever increasing, especially in ...
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This book explains classical statistical analyses of clinical trials,andaddresses relatively novel issues, including equivalence ...
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The second edition of this popular guide demonstrates the process of entering and analyzing data using the latest version ...
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