Applied Regression Analysis for Business and Economics

Designed for undergraduate and MBA courses in regression analysis for business and economics, this text requires very little mathematical expertise beyond college algebra. Terry Dielman 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.

About the Author:

Terry Dielman is professor of Decision Sciences at Texas Christian University. Terry received his Ph.D. at the University of Michigan (Business Statistics), his M.S. at the University of Cincinnati (Mathematics) and his B.A. at Emporia State University (Mathematics). His recent research focuses on Regression Analysis, Time Series Forecasting, Robust Statistical Procedures and the Analysis of Pooled Cross–Sectional and Time Series Data. His recent publications include Bootstrap versus Traditional Hypothesis Testing Procedures for Coefficients in Least Absolute Value Regression in the JOURNAL OF STATISTICAL COMPUTATION AND SIMULATION. He participates in the Editorial Board of the Journal of Business and Management, and consults for Forecasting Seminars and for various law firms.