Applied Regression Analysis

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John Wiley & Sons, Aug 25, 2014 - Mathematics - 736 pages
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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.

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1Fitting aStraight Line by Least Squares
7The AlgebraandGeometry of Pure
Straight Line Case
The General Regression Situation
6Extra Sumsof Squares and Tests for Several
7Serial Correlation in the Residuals and the Durbin
18Generalized Linear Models GLIM
Mixture Ingredients as Predictor Variables
20The Geometry of Least Squares
More Geometry of Least Squares
Orthogonal Polynomials and Summary Data
Multiple Regression Applied to Analysis of Variance
AnIntroduction to Nonlinear Estimation

Exercises for Chapter
More on Checking Fitted Models
Special Topics
Biasin Regression Estimates and Expected Values
4Expected Value of Extra Sum of Squares
Dummy Variables 14 1 DummyVariables to Separate
15Selecting the Best Regression Equation
Models Containing Functions of the Predictors
Robust Regression
TrueFalse Questions
Answers to Exercises
Index of Authors Associated with Exercises

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About the author (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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