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.
Preface ........................................................................................................................... 1
Chapter 1 Basics of regression models .................................................................. 2
1.1. Types and applications of regression models. .............................................................................. 2
1.2. Basic elements of a single-equation linear regression model. ..................................................... 4
Chapter 2 Relevance of outlying and influential observations for regression analysis ..................................................................................................... 7
2.1. Nature and dangers of univariate and multivariate outlying observatlƒq
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