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 Author Freund, Rudolf J Title Regression Analysis : Statistical Modeling of a Response Variable Imprint Burlington : Elsevier Science & Technology, 2006 ©2006
 Edition 2nd ed Descript 1 online resource (481 pages) text txt rdacontent computer c rdamedia online resource cr rdacarrier Series Regression Analysis Ser Regression Analysis Ser Note Front Cover -- Regression Analysis: Statistical Modeling of a Response Variable -- Copyright Page -- Contents -- Preface -- An Overview -- Part I: The Basics -- Chapter 1. The Analysis of Means: A Review of Basics and an Introduction to Linear Models -- 1.1 Introduction -- 1.2 Sampling Distributions -- 1.3 Inferences on a Single Population Mean -- 1.4 Inferences on Two Means Using Independent Samples -- 1.5 Inferences on Several Means -- 1.6 Summary -- 1.7 Chapter Exercises -- Chapter 2. Simple Linear Regression: Linear Regression with one Independent Variable -- 2.1 Introduction -- 2.2 The Linear Regression Model -- 2.3 Inferences on the Parameters ß0 and ß1 -- 2.4 Inferences on the Response Variable -- 2.5 Correlation and the Coefficient of Determination -- 2.6 Regression through the Origin -- 2.7 Assumptions on the Simple Linear Regression Model -- 2.8 Uses and Misuses of Regression -- 2.9 Inverse Predictions -- 2.10 Summary -- 2.11 Chapter Exercises -- Chapter 3. Multiple Linear Regression -- 3.1 Introduction -- 3.2 The Multiple Linear Regression Model -- 3.3 Estimation of Coefficients -- 3.4 Interpreting the Partial Regression Coef.cients -- 3.5 Inferences on the Parameters -- 3.6 Testing a General Linear Hypothesis (Optional Topic) -- 3.7 Inferences on the Response Variable in Multiple Regression -- 3.8 Correlation and the Coef.cient of Determination -- 3.9 Getting Results -- 3.10 Summary and a Look Ahead -- 3.11 Chapter Exercises -- Part II: Problems and Remedies -- Chapter 4. Problems with Observations -- 4.1 Introduction -- 4.2 Outliers and Influential Observations -- 4.3 Unequal Variances -- 4.4 Robust Estimation -- 4.5 Correlated Errors -- 4.6 Summary -- 4.7 Chapter Exercises -- Chapter 5. Multicollinearity -- 5.1 Introduction -- 5.2 The Effects of Multicollinearity -- 5.3 Diagnosing Multicollinearity -- 5.4 Remedial Methods 5.5 Summary -- 5.6 Chapter Exercises -- Chapter 6. Problems with the Model -- 6.1 Introduction -- 6.2 Specification Error -- 6.3 Lack of Fit Test -- 6.4 Overspeci.cation: Too Many Variables -- 6.5 Variable Selection Procedures -- 6.6 Reliability of Variable Selection -- 6.7 Usefulness of Variable Selection -- 6.8 Variable Selection and Influential Observations -- 6.9 Summary -- 6.10 Chapter Exercises -- Part III: Additional Uses of Regression -- Chapter 7. Curve Fitting -- 7.1 Introduction -- 7.2 Polynomial Models with One Independent Variable -- 7.3 Segmented Polynomials with Known Knots -- 7.4 Polynomial Regression in Several Variables -- Response Surfaces -- 7.5 Curve Fitting without a Model -- 7.6 Summary -- 7.7 Chapter Exercises -- Chapter 8. Introduction to Nonlinear Models -- 8.1 Introduction -- 8.2 Intrinsically Linear Models -- 8.3 Intrinsically Nonlinear Models -- 8.4 Summary -- 8.5 Chapter Exercises -- Chapter 9. Indicator Variables -- 9.1 Introduction -- 9.2 The Dummy Variable Model -- 9.3 Unequal Cell Frequencies -- 9.4 Empty Cells -- 9.5 Models with Dummy and Continuous Variables -- 9.6 A Special Application: The Analysis of Covariance -- 9.7 Heterogeneous Slopes in the Analysis of Covariance -- 9.8 Summary -- 9.9 Chapter Exercises -- Chapter 10. Categorical Response Variables -- 10.1 Introduction -- 10.2 Binary Response Variables -- 10.3 Weighted Least Squares -- 10.4 Simple Logistic Regression -- 10.5 Multiple Logistic Regression -- 10.6 Loglinear Model -- 10.7 Summary -- 10.8 Chapter Exercises -- Chapter 11. Generalized Linear Models -- 11.1 Introduction -- 11.2 The Link Function -- 11.3 The Logistic Model -- 11.4 Other Models -- 11.5 Summary -- Appendix A: Statistical Tables -- A.1 The Standard Normal Distribution-Probabilities Exceeding Z -- A.2 The T Distribution-Values of T Exceeded with Given Probability A.3 The X2 Distribution-X2 Values Exceeded with Given Probability -- A.4 The F Distribution p= 0.1 -- A.5 The Durbin-Watson Test Bounds -- Appendix B: A Brief Introduction Tomatrices -- B.1 Matrix Algebra -- B.2 Solving Linear Equations -- Appendix C: Estimation Procedures -- C.1 Least Squares Estimation -- C.2 Maximum Likelihood Estimation -- References -- Index Complete discussion of analysis of data including estimation, diagnostics, and remedial actions Description based on publisher supplied metadata and other sources Electronic reproduction. Ann Arbor, Michigan : ProQuest Ebook Central, 2020. Available via World Wide Web. Access may be limited to ProQuest Ebook Central affiliated libraries Link Print version: Freund, Rudolf J. Regression Analysis : Statistical Modeling of a Response Variable Burlington : Elsevier Science & Technology,c2006 9781493300013 Subject Regression analysis.;Linear models (Statistics) Electronic books Alt Author Wilson, William J Sa, Ping
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