Analysis of Variance

Klaus Backhaus (), Bernd Erichson (), Sonja Gensler (), Rolf Weiber () and Thomas Weiber ()
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Klaus Backhaus: University of Münster
Bernd Erichson: Otto-von-Guericke-University Magdeburg
Sonja Gensler: University of Münster
Rolf Weiber: University of Trier

Chapter Chapter 3 in Multivariate Analysis, 2021, pp 147-203 from Springer

Abstract: Abstract Analysis of variance is a procedure that examines the effect of one (or more) independent variable(s) on one (or more) dependent variable(s). For the independent variables, which are also called factors or treatments, only a nominal scaling is required, while the dependent variable (also called target variable) is scaled metrically. The analysis of variance is the most important multivariate method for the detection of mean differences across more than two groups and is thus particularly useful for the evaluation of experiments. The chapter deals with both the one-factorial (one dependent and one independent variable) and the two-factorial (one dependent and two independent variables) analysis of variance and extends the considerations in the case study to the analysis with two (nominally scaled) independent factors and two (metrically scaled) covariates. Furthermore, contrast analysis and post-hoc testing are also covered.

Date: 2021
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DOI: 10.1007/978-3-658-32589-3_3

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