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Applied linear statistical models : Michael H. Kutner ... [et al.]

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. Updated throughout to include the latest developments and methods in statistics such as advanced bootstrapping, neural networks, regression trees, other blocking approaches, Taguchi Methodology, and more. . A new Chapter 15, Introduction to the Design of Experiments and Observational Studies provides a basic framework for the design and analysis of scientific studies. .The flow has been improved throughout, combining related chapters and smoothing transitions between concepts. Overall, the text has been reduced from 32 chapters to 30 with one entirely new chapter. .New open ended ’Cases’ based on data sets from business, health care, and engineering are included. Also, many problem data sets have been updated and expanded. .The text includes a CD with all data sets and the Student Solutions manual in PDF. In addition a new supplement, SAS and SPSS Program Solutions by Replogle and Johnson is available for the Fifth Edition. .Applied Linear Statistical Models contains all chapters in the Applied Linear Regression Models Fourth Edition, plus an additional 16 chapters on single and multifactor ANOVA and Experimental Design. The standard regression framework is emphasized throughout the text. .Expanded discussion of model selection methods and criteria including Akaike Information Criterion and the Schwarz Bayesian Criterion. .Extensively revised coverage of logistic regression, including polytomous nominal and ordinal logistic regression models.

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