Applied Regression Analysis

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John Wiley & Sons, 25 ago 2014 - 736 pagine
An outstanding introduction to the fundamentals of regression analysis-updated and expanded The methods of regression analysis are the most widely used statistical tools for discovering the relationships among variables. This classic text, with its emphasis on clear, thorough presentation of concepts and applications, offers a complete, easily accessible introduction to the fundamentals of regression analysis. Assuming only a basic knowledge of elementary statistics, Applied Regression Analysis, Third Edition focuses on the fitting and checking of both linear and nonlinear regression models, using small and large data sets, with pocket calculators or computers. This Third Edition features separate chapters on multicollinearity, generalized linear models, mixture ingredients, geometry of regression, robust regression, and resampling procedures. Extensive support materials include sets of carefully designed exercises with full or partial solutions and a series of true/false questions with answers. All data sets used in both the text and the exercises can be found on the companion disk at the back of the book. For analysts, researchers, and students in university, industrial, and government courses on regression, this text is an excellent introduction to the subject and an efficient means of learning how to use a valuable analytical tool. It will also prove an invaluable reference resource for applied scientists and statisticians.
 

Sommario

Basic Prerequisite Knowledge
1
Fitting a Straight Line by Least Squares
15
Checking the Straight Line Fit
47
Appendix 2B MINITAB Instructions
76
Exercises for Chapters 13
96
Straight Line Case
115
Exercises for Chapter 4
132
Appendix 5A Selected Useful Matrix Results
147
149
364
IllConditioning in Regression Data
369
More Geometry of Least Squares
447
Orthogonal Polynomials and Summary Data
461
An Introduction to Nonlinear Estimation
505
401
519
Robust Regression
567
Resampling Procedures Bootstrapping
585

Serial Correlation in the Residuals and the DurbinWatson Test
179
More on Checking Fitted Models
205
Special Topics
217
Bias in Regression Estimates and Expected Values of Mean
235
Exercises for Chapter 10
241
Models Containing Functions of the Predictors Including
251
Exercises for Chapter 12
272
Dummy Variables
299
Selecting the Best Regression Equation
327
Bibliography
593
409
596
TrueFalse Questions
605
427
684
Index of Authors Associated with Exercises
695
585
698
605
705
Copyright

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Informazioni sull'autore (2014)

NORMAN R. DRAPER teaches in the Department of Statistics at the University of Wisconsin. HARRY SMITH is a former faculty member of the Mt. Sinai School of Medicine.

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