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Analysis of Variance

In: Handbook of Market Research

Author

Listed:
  • Jan R. Landwehr

    (Goethe University Frankfurt)

Abstract

Experiments are becoming increasingly important in marketing research. Suppose a company has to decide which of three potential new brand logos should be used in the future. An experiment in which three groups of participants rate their liking of one of the logos would provide the necessary information to make this decision. The statistical challenge is to determine which (if any) of the three logos is liked significantly more than the others. The adequate statistical technique to assess the statistical significance of such mean differences between groups of participants is called analysis of variance (ANOVA). The present chapter provides an introduction to the key statistical principles of ANOVA and compares this method to the closely related t-test, which can alternatively be used if exactly two means need to be compared. Moreover, it provides introductions to the key variants of ANOVA that have been developed for use when participants are exposed to more than one experimental condition (repeated-measures ANOVA), when more than one dependent variable is measured (multivariate ANOVA), or when a continuous control variable is considered (analysis of covariance). This chapter is intended to provide an applied introduction to ANOVA and its variants. Therefore, it is accompanied by an exemplary dataset and self-explanatory command scripts for the statistical software packages R and SPSS, which can be found in the Web-Appendix.

Suggested Citation

  • Jan R. Landwehr, 2022. "Analysis of Variance," Springer Books, in: Christian Homburg & Martin Klarmann & Arnd Vomberg (ed.), Handbook of Market Research, pages 265-297, Springer.
    • Handle: RePEc:spr:sprchp:978-3-319-57413-4_16
    DOI: 10.1007/978-3-319-57413-4_16
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