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Regression Analysis

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A Concise Guide to Market Research

Part of the book series: Springer Texts in Business and Economics ((STBE))

Learning Objectives

After reading this chapter, you should understand:

  • What regression analysis is and what it can be used for.

  • How to specify a regression analysis model.

  • How to interpret basic regression analysis results.

  • What the issues with, and assumptions of regression analysis are.

  • How to validate regression analysis results.

  • How to conduct regression analysis in SPSS.

  • How to interpret regression analysis output produced by SPSS.

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Notes

  1. 1.

    Strictly speaking, the difference between predicted and observed y-values is \(\hat e\).

  2. 2.

    This only applies to the standardized βs.

  3. 3.

    Rules of thumb are almost never without issues. For Green’s formula, these are that you need a larger sample size than he proposes if you expect small effects (an expected R2 of 0.10 or smaller). In addition, if the variables are poorly measured, or if you want to use a stepwise method, you need a larger sample size. With “larger” we mean around three times the required sample size if the expected R2 is low, and about twice the required sample size in case of measurement errors or if stepwise methods are used.

  4. 4.

    The tolerance is calculated using a completely separate regression analysis. In this regression analysis, the variable for which the tolerance is calculated is taken as a dependent variable and all other independent variables are entered as independents. The R2 that results from this model is deducted from 1, thus indicating how much is not explained by the regression model. If very little is not explained by the other variables, (multi) collinearity is a problem.

  5. 5.

    An interesting perspective on significance and effect sizes is offered by Cohen’s (1994) classical article “The Earth is Round (p <.05).

  6. 6.

    For an application of the ACSI, see, for example, Ringle et al. (2010).

  7. 7.

    You can download the reduced dataset ACSI Data_without outlier.sav in the Web Appendix (Chap. 7)

  8. 8.

    We would like to thank Dr. D.I. Gilliland and AgriPro for making the data and case study available.

References

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Author information

Authors and Affiliations

  1. Faculty of Economics and Management, Otto-von-Guericke-Universität, Magdeburg, Germany

    Marko Sarstedt

  2. Faculty of Business and Law, University of Newcastle, Callaghan, Australia

    Marko Sarstedt

  3. Faculty of Business and Economics, University of Melbourne, Parkville, Victoria, Australia

    Erik Mooi

  4. Aston Business School, University of Aston, Birmingham, UK

    Erik Mooi

Authors
  1. Marko Sarstedt
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  2. Erik Mooi
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Sarstedt, M., Mooi, E. (2014). Regression Analysis. In: A Concise Guide to Market Research. Springer Texts in Business and Economics. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-53965-7_7

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