Levene's Test of Equal Variances (Part 1) - Homogeneity of Variance TestLevene's test of Equal Variances is covered in this video, including:How to interpret
The F-test statistic is a generalization of the t-test statistic, and is a scalar random variable. The F-test statistic can be calculated as a ratio of the variances of two samples, and so can be used to test whether or not data samples come from populations with equal variances. The F-Test statistic and p-value will be calculated so that youOne approach would be to attempt to use the F-test for testing equality of population variances or another method to verify the homogeneity assumption before applying the equal variance t-test (Moser and Stevens, 1992). If the hypothesis of equal variances is not rejected, then one would apply the “usual” t-test. If the hypothesis of equal5. F-Test Fisher’s Test Basic assumption is that data is normal. Any statistical test in which the test statistic has an F-distribution under the null hypothesis. Levene’s Test An inferential statistic used to assess the equality of variances in different samples. Test is robust to non-normal data. Some common statistical procedures assume
1) Perform a Shapiro-Wilk test to assess normality. 2) If the data is not normal, perform Levene's test of equal variance. If the data is normal, an F-test. 3) Perform a Mann-Whitney Test (Wilcoxon Test) to compare difference in means. Or alternatively, Welch's t-test if the data is normal. My concerns:
Instead, it is standard practice to avoid doing a test for equal variances and then branching to either a pooled 2-sample t test (which requires equal population variances) and a Welch 2-sample t test (which does not assume equal variances). One of several reasons for deprecating such a tandem-test procedure is that the variance test has poor
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