Kutner, Nachtsheim, Neter, Wasserman, Applied Linear Regression Models, 4/e (ALRM4e) is the long established leading authoritative text and reference on regression (previously Neter was lead author.) For students in most any discipline where statistical analysis or interpretation is used, ALRM has served as the industry standard. The text includes brief introductory and review material, and then proceeds through regression and modeling. All topics are presented in a precise and clear style supported with solved examples, numbered formulae, graphic illustrations, and "Comments" to provide depth and statistical accuracy and precision. Applications used within the text and the hallmark problems, exercises, and projects are drawn from virtually all disciplines and fields providing motivation for students in any discipline. ALRM 4e provides an increased use of computing and graphical analysis throughout, without sacrificing concepts or rigor.
Part1 Simple Linear Regression
1Linear Regression with One Predictor Variable
2Inferences in Regression and Correlation Analysis
3Diagnostics and Remedial Measures
4 Simultaneous Inferences and Other Topics in Regression Analysis
5Matrix Approach to Simple Linear Regression Analysis
Part 2Multiple Linear Regression
6Multiple Regression I
7 Multiple Regression II
8Building the Regression Model I: Models for Quantitative and Qualitative Predictors
9 Building the Regression Model II: Model Selection and Validation
10Building the Regression Model III: Diagnostics
11Remedial Measures and Alternative Regression Techniques
12Autocorrelation in Time Series Data
Part 3Nonlinear Regression
13Introduction to Nonlinear Regression and Neural Networks
14Logistic Regression, Poisson Regression, and Generalized Linear Models