If p < 0.05, the interaction between gender and training has a statistically significant effect on a test score. Moreover, we should look at the p-value in row Gender*Training. Tests of between-subjects effects show how the dependent variables (English test score, Math test score, History test score) differ for the interaction between Gender and Training.
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How to Report CTests of between-subjects Table in SPSS output? In addition, If we look at the p-value for Wilks’ Lambda in Gender row (p = 0.636), we fail to reject the null hypothesis and conclude that there is no effect of gender on test scores (English, Maths, History).įinally, If we look p-value for Wilks’ Lambda in Training row (p = 0.010), we must reject the null hypothesis and conclude that there is the effect of training on test scores (English, Maths, History).
So, we fail to reject the null hypothesis and conclude that there is no statistically significant effect of the interaction of gender and training on test scores (English, Maths, History). Therefore, there is a statistically significant effect of the interaction of gender and training on test scores (English, Maths, History).įor example, our p-value is 0.512. Secondly, if our p-value is lower than 0.05. Therefore, there is no statistically significant effect of the interaction of gender and training on test scores (English, Maths, History). So, we should look at the results of Wilk’s Lambda test in the row for the interaction between Gender and Training.įirstly, If our p-value is greater than 0.05. Multivariate Tests show the results of Wilk’s Lambda test. How to Report Multivariate Tests Table SPSS Output? There is an effect of interaction between the two independent categorical variables on the two or more continuous dependent variables.ĭo you need to help with how to run the Two-way MANOVA test in SPSS? There is no effect of interaction between the two independent categorical variables on the two or more continuous dependent variables. Therefore, we have two independent categorical variables: Gender (male and female) and training (1 or 2 or 3 months) and three continuous dependent variables (English test score, Math test score, and History test score). We want to examine whether there is an interaction effect of gender and training on English test scores, Math test scores, and History test scores.
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This guide will explain, step by step, how to run the Two-way MANOVA test in SPSS statistical software by using an example.
Two-way multivariate analysis of variance (MANOVA) deals with testing the effects of the two grouping variables, usually called factors, on the measured observations as well as interaction effects between the factors. This easy tutorial will show you how to run the Two Way MANOVA test in SPSS, and how to interpret the result. Using the Two-Way MANOVA test in Research