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Regression Analysis

In: Handbook of Market Research

Author

Listed:
  • Bernd Skiera

    (Goethe University Frankfurt)

  • Jochen Reiner

    (Goethe University Frankfurt)

  • Sönke Albers

    (Kuehne Logistics University)

Abstract

Linear regression analysis is one of the most important statistical methods. It examines the linear relationship between a metric-scaled dependent variable (also called endogenous, explained, response, or predicted variable) and one or more metric-scaled independent variables (also called exogenous, explanatory, control, or predictor variable). We illustrate how regression analysis work and how it supports marketing decisions, e.g., the derivation of an optimal marketing mix. We also outline how to use linear regression analysis to estimate nonlinear functions such as a multiplicative sales response function. Furthermore, we show how to use the results of a regression to calculate elasticities and to identify outliers and discuss in details the problems that occur in case of autocorrelation, multicollinearity and heteroscedasticity. We use a numerical example to illustrate in detail all calculations and use this numerical example to outline the problems that occur in case of endogeneity.

Suggested Citation

  • Bernd Skiera & Jochen Reiner & Sönke Albers, 2022. "Regression Analysis," Springer Books, in: Christian Homburg & Martin Klarmann & Arnd Vomberg (ed.), Handbook of Market Research, pages 299-327, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-57413-4_17
    DOI: 10.1007/978-3-319-57413-4_17
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