You want to tell your reader what type of analysis you conducted. This will help your reader make sense of your results. You also want to tell your reader why this particular analysis was used. What did your analysis test for?
Repeated-Measures ANOVA in SPSS, Including Interpretation
Multivariate Analysis of Variance (MANOVA)
In this section, we show you only the main tables required to understand your results from the one-way MANOVA and Tukey post-hoc tests. This includes relevant boxplots, scatterplot matrix and Pearson's correlation coefficients, and output from your Mahalanobis distance test, Shapiro-Wilk test for normality, and Box's M test of equality of covariance, and if required, Levene's test of homogeneity of variance. However, in this "quick start" guide, we focus only on the four main tables you need to understand your one-way MANOVA results, assuming that your data has already met the nine assumptions required for a one-way MANOVA to give you a valid result. The first important one is the Descriptive Statistics table shown below.
The p-values for the production method are statistically significant at the 0. The p-values for the manufacturing plant are not significant at the 0. The p-values for the interaction between plant and method are statistically significant at the 0. Because the interaction is statistically significant, the effect of the method depends on the plant.
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