APPLIED REGRESSION ANALYSIS focuses on the application of regression to real data and examples while employing commercial statistical and spreadsheet software. Designed for both business/economics undergraduates and MBAs, this text provides all of the core regression topics as well as optional topics including ANOVA, Time Series Forecasting, and Discriminant Analysis. While only a prior introductory statistics course is required, a review of all necessary basic statistics is provided in chapter 2. The text emphasizes the importance of understanding the assumptions of the regression model, knowing how to validate a selected model for these assumptions, knowing when and how regression might be useful in a business setting, and understanding and interpreting output from statistical packages and spreadsheets.
Ch.1 An Introduction to Regression Analysis
Ch.2 Review of Basic Statistical Concepts
Ch.3 Simple Regression Analysis
Ch.4 Multiple Regression Analysis
Ch.5 Fitting Curves to Data
Ch.6 Assessing the Assumptions of the Regression Model
Ch.7 Using Indicator and Interaction Variables
Ch.8 Variable Selection
Ch.9 An Introduction to Analysis of Variance
Ch.10 Qualitative Dependent Variables: An Introduction to Discriminant Analysis and Logistic Regression
Ch.11 Forecasting Methods for Time-Series Data
APPENDICES
A. Summation Notation
B. Statistical Tables
C. A Brief Introduction to MINITAB, Microsoft Excel, and SAS
D. Matrices and their Application to Regression Analysis
E. Solutions to Selected Odd-Numbered Exercises
REFERENCES / INDEX