About this product

Product Information

This new edition of Applied Linear Statistical Models retains the book's uniquely straightforward writing style and format while providing you with the latest information and knowledge. Updates include developments and methods in partial regression and residual plots, an entirely new introduction to the Design of Experiments section that frames and outlines the organization and concepts of design and ANOVA, and more.

Product Identifiers

PublisherMcGraw-Hill Higher Education

ISBN-100072386886

ISBN-139780072386882

eBay Product ID (ePID)30277718

Product Key Features

Number of Pages1424 Pages

Publication NameApplied Linear Statistical Models

LanguageEnglish

SubjectProbability & Statistics / General, Probability & Statistics / Regression Analysis, Statistics, Research & Methodology

Publication Year2004

TypeTextbook

AuthorJohn Neter, Michael H. Kutner, William Li, Chris J. Nachtsheim

Subject AreaBusiness & Economics, Science, Mathematics

SeriesThe Mcgraw-Hill/Irwin Series Operations and Decision Sciences

FormatHardcover

Dimensions

Item Height2.1 in

Item Weight35.7 Oz

Item Length9.4 in

Item Width7.5 in

Additional Product Features

Edition Number5

LCCN2004-052447

Dewey Edition22

Target AudienceCollege Audience

IllustratedYes

Dewey Decimal519.5/36

Lc Classification NumberQa278.2.K87 2005

Table of ContentPart1 Simple Linear Regression 1 Linear Regression with One Predictor Variable 2 Inferences in Regression and Correlation Analysis 3 Diagnostics and Remedial Measures 4 Simultaneous Inferences and Other Topics in Regression Analysis 5 Matrix Approach to Simple Linear Regression Analysis Part 2 Multiple Linear Regression 6 Multiple Regression I 7 Multiple Regression II 8 Regression Models for Quantitative and Qualitative Predictors 9 Building the Regression Model I: Model Selection and Validation 10 Building the Regression Model II: Diagnostics 11 Building the Regression Model III: Remedial Measures 12 Autocorrelation in Time Series Data Part 3 NonLinear Regression 13 Introduction to Nonlinear Regression and Neural Networks 14 Logistic Regression, Poisson Regression, and Generalized Linear Models Part 4 Design and Analysis of Single-Factor Studies 15 Introduction to the Design of Experimental and Observational Studies 16 Single-Factor Studies 17 Analysis of Factor Level Means 18 ANOVA Diagnostics and Remedial Measures Part 5 Multi-Factor Studies 19 Two-Factor Studies with Equal Sample Sizes 20 Two-Factor Studies-One Case per Treatment 21 Randomized Complete Block Designs 22 Analysis of Covariance 23 Two-Factor Studies with Unequal Sample Sizes 24 Multifactor Studies 25 Random and Mixed Effects Models Part 6 Specialized Study Designs 26 Nested Designs, Subsampling, and Partially Nested Designs 27 Repeated Measures and Related Designs 28 Balanced Incomplete Block, Latin Square, and Related Designs 29 Exploratory Experiments: Two-Level Factorial and Fractional Factorial Designs 30 Response Surface Methodology Appendix A: Some Basic Results in Probability and Statistics Appendix B: Tables Appendix C: Data Sets Appendix D: Rules for Developing ANOVA Models and Tables for Balanced Designs Appendix E: Selected Bibliography

The McGraw-Hill/Irwin Series Operations and Decision Sciences: Applied Linear Statistical Models by Chris J. Nachtsheim, Michael H. Kutner, William Li and John Neter (2004, Hardcover)