Regression Analysis and its Application

Providing a better understanding of classical regression analysis, this book bridges the gap between the purely theoretical coverage of regression analysis and its practical application. It presents regression analysis in the general context of data analysis. Using a teach-by-example format, the text contains ten major data sets along with several smaller ones to illustrate the common characteristics of regression data and properties of statistics that are employed in regression analysis. The book covers model misspecification, residual analysis, multicollinearity, biased regression estimators, data collection, model assumptions, and the interpretation of parameter estimates.