Applied Linear Regression

Abstract

3rd ed. Applied Linear Regression, Third Edition is thoroughly updated to help students master the theory and applications of linear regression modeling. Focusing on model building, assessing fit and reliability, and drawing conclusions, the text demonstrates how to develop estimation, confidence, and testing procedures primarily through the use of least squares regression. Scatterplots and regression -- Simple linear regression -- Multiple regression -- Drawing conclusions -- Weights, lack of fit, and more -- Polynomials and factors -- Transformations -- Regression diagnostics : residuals -- Outliers and influence -- Variable selection -- Nonlinear regression -- Logistic regression. Applied Linear Regression; Contents; Preface; 1 Scatterplots and Regression; 1.1 Scatterplots; 1.2 Mean Functions; 1.3 Variance Functions; 1.4 Summary Graph; 1.5 Tools for Looking at Scatterplots; 1.5.1 Size; 1.5.2 Transformations; 1.5.3 Smoothers for the Mean Function; 1.6 Scatterplot Matrices; Problems; 2 Simple Linear Regression; 2.1 Ordinary Least Squares Estimation; 2.2 Least Squares Criterion; 2.3 Estimating σ(2); 2.4 Properties of Least Squares Estimates; 2.5 Estimated Variances; 2.6 Comparing Models: The Analysis of Variance; 2.6.1 The F-Test for Regression.