Analysis of variance is the most common inferential statistical procedure used to analyze experiments because
A)it is the only statistical procedure that can test either between-subjects factors or within-subjects factors.
B)there are several different versions of it,and so it can test for possible treatment effects more accurately than the two-sample tests.
C)most researchers are more interested in whether there are differences in the variance among the conditions than in whether there are differences in the means.
D)there are several different versions of it,and so it can be used with many different experimental designs.

Question

Quizplus · Accepted Answer

Analysis of variance (ANOVA) is a versatile statistical procedure that can be used with several different experimental designs, such as one-way ANOVA, two-way ANOVA, and repeated measures ANOVA. It allows researchers to compare multiple means simultaneously and test for the significance of treatment effects while controlling for the error variance. ANOVA is also preferred over two-sample tests (e.g., t-tests) when dealing with more than two groups, as it reduces the risk of committing a Type I error (i.e., rejecting the null hypothesis when it is true). Therefore, option D is the best choice as it explains how the multiple versions of ANOVA make it useful and applicable for different experimental designs.

Analysis of Variance Is the Most Common Inferential Statistical Procedure