Applied Linear Statistical Models: Applied Linear Regression Models (5版)

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書名：Applied Linear Statistical Models: Applied Linear Regression Models 5/e 作者：KUTNER 出版社：McGraw-Hill 出版日期：2019/09/00 ISBN：9789863414179 內容簡介 　　1. Added material on important techniques for data mining, including regression trees and neural network models in Chapters 11 and 13. 　　2. The Chapter on logistic regression (Chapter 14) has been extensively revised and expanded to include a more thorough treatment of logistic, probit, and complementary log-log models, logistic regression residuals, model selection, model assessment, logistic regression diagnostics, and goodness of fit tests. We have also developed new material on polytomous (multicategory) nominal logistic regression models and polytomous ordinal logistic regression models. 　　3. We have expanded the discussion of model selection methods and criteria. The Akaike information criterion and Schwarz Bayesian criterion have been added, and a greater emphasis is placed on the use of cross-validation for model selection and validation. 　　4. 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. 　　5. 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. 目錄 PART I: SIMPLE LINEAR REGRESSION Ch 1 Linear Regression with One Predictor Variable Ch 2 Inferences in Regression and Correlation Analysis Ch 3 Diagnostics and Remedial Measures Ch 4 Simultaneous Inferences and Other Topics in Regression Analysis Ch 5 Matrix Approach to Simple Linear Regression Analysis PART II: MULTIPLE LINEAR REGRESSION Ch 6 Multiple Regression I Ch 7 Multiple Regression II Ch 8 Regression Models for Quantitative and Qualitative Predictors Ch 9 Building the Regression Model I: Model Selection and Validation Ch10 Building the Regression Model II: Diagnostics Ch11 Building the Regression Model III: Remedial Measures Ch12 Autocorrelation in Time Series Data PART III: NONLINEAR REGRESSION Ch13 Introduction to Nonlinear Regression and Neural Networks Ch14 Logistic Regression, Poisson Regression, and Generalized Linear Models

Applied Linear Statistical Models: Design and Analysis of Experiments (5版)

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書名：Applied Linear Statistical Models: Design and Analysis of Experiments 5/e 作者：KUTNER 出版社：McGraw-Hill 出版日期：2019/09/00 ISBN：9789863414186 內容簡介 　　1. Applied Linear Statistical Models contains 14 chapters on the Applied Linear Regression Models, plus an additional 16 chapters on single and multifactor ANOVA and Experimental Design. The standard regression framework is emphasized throughout the text. 　　2. 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. 　　3. 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. 　　4. 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. 　　5. 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. 目錄 PART IV: DESIGN AND ANALYSIS OF SINGLE-FACTOR STUDIES Ch15 Introduction to the Design of Experimental and Observational Studies Ch16 Single Factor Studies Ch17 Analysis of Factor Level Means Ch18 ANOVA Diagnostics and Remedial Measures PART V: MULTI-FACTOR STUDIES Ch19 Two-Factor Studies with Equal Sample Sizes Ch20 Two-Factor Studies-One Case per Treatment Ch21 Randomized Complete Block Designs Ch22 Analysis of Covariance Ch23 Two-Factor Studies with Unequal Sample Sizes Ch24 Multi-Factor Studies Ch25 Random and Mixed Effects Models PART VI: SPECIALIZED STUDY DESIGNS Ch26 Nested Designs, Subsampling, and Partially Nested Designs Ch27 Repeated Measures and Related Designs Ch28 Balanced Incomplete Block, Latin Square, and Related Designs Ch29 Exploratory Experiments: Two-Level Factorial and Fractional Factorial Designs Ch30 Response Surface Methodology