A test for independence of the variables shown in the table below (alternative vs.

This is a chi-square test of independence, used in the Analyze Phase to determine whether two categorical variables are related. The null hypothesis states that the variables are independent, while the alternative hypothesis states that they are dependent. The table shows 6 result categories (M, N, O, P, Q, R) and 2 alternative categories (A, B), so the degrees of freedom are calculated as (rows − 1) × (columns − 1) = (6 − 1) × (2 − 1) = 5. For α = 0.05 and 5 degrees of freedom, the critical chi-square value is 11.07. The test statistic given is χ² = 17.0. Since 17.0 is greater than 11.07, the result falls in the rejection region, so the null hypothesis must be rejected. That means there is sufficient statistical evidence to conclude that the variables are not independent and are therefore dependent. In Six Sigma analysis, this kind of result indicates that category membership in one variable is associated with category membership in the other, which can guide further root-cause investigation and decision-making.