Preface.- Basics of regression models.- Relevance of outlying and influential observations for regression analysis.- Basic procedure for multiple regression model building -- Verification of multiple regression model -- Common adjustments to multiple regressions -- Common pitfalls in regression analysis -- Regression analysis of discrete dependent variables -- Real-life case-study: The quarterly sales revenues of Nokia Corporation -- Real-life case-study: Identifying overvalued and undervalued airlines -- Appendix: Statistical Tables.

This book offers hands-on statistical tools for business professionals by focusing on the practical application of a single-equation regression. The authors discuss commonly applied econometric procedures, which are useful in building regression models for economic forecasting and supporting business decisions. A significant part of the book is devoted to traps and pitfalls in implementing regression analysis in real-world scenarios. The book consists of nine chapters, the final two of which are fully devoted to case studies. Today's business environment is characterised by a huge amount of economic data. Making successful business decisions under such data-abundant conditions requires objective analytical tools, which can help to identify and quantify multiple relationships between dozens of economic variables. Single-equation regression analysis, which is discussed in this book, is one such tool. The book offers a valuable guide and is relevant in various areas of economic and business analysis, including marketing, financial and operational management.