An F-test is a statistical method used in Six Sigma to compare the variances of two or more groups to determine if they are significantly different. It is commonly used in analysis of variance (ANOVA) to test the null hypothesis that the variances are equal. The F-test calculates the F-ratio, which is the ratio of the variances between the groups to the variance within the groups. By comparing the F-ratio to a critical value from the F-distribution, you can assess the likelihood of the observed differences occurring by chance. F-tests are essential for identifying significant factors in process improvement and ensuring data-driven decisions.
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