One Way Anova Test Example. Select response data are in one column for all factor levels. To see if there is a statistically significant difference in mean exam scores we can conduct a one way anova.
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At least one population mean is different from the rest. Hence 25 17 mstr 43024 78 f mse 1709. To test the effect of cause x on the ctq y.
μ 1 μ 2 μ 3 μ k all the population means are equal h 1 null hypothesis.
To see if there is a statistically significant difference in mean exam scores we can conduct a one way anova. Reporting the results of a one way anova we found a statistically significant difference in average crop yield according to fertilizer type f 2 9 073 p 0 001. For example we might want to know if three different studying techniques lead to different mean exam scores. Example of one way anova.
