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Test for Equal VariancesStat > ANOVA > Test for Equal Variances
Use to assess the equality (also called the homogeneity) of the variances or the standard deviations of multiple populations. For example, a lumber distributor wants to compare the variation of beams that are cut by three different sawmills. The distributor measures the length of the beams to determine whether the consistency of the beam lengths differs among the sawmills.
Both the variance and the standard deviation measure the variability in a sample or a population. (The standard deviation is the square root of the variance.) If the variances are significantly different, then the standard deviations are also significantly different, and vice versa.
Many statistical procedures, including analysis of variance (ANOVA), assume that although different samples may come from populations with different means, they have the same variance. The effect of unequal variances upon inferences depends in part on whether your model includes fixed or random factors, disparities in sample sizes, and the choice of multiple comparison procedure. An ANOVA is only slightly affected by inequality of variance if the model contains only fixed factors and has equal or nearly equal sample sizes. An ANOVA with random effects may be substantially affected, however [28].
Response data are in one column for all factor levels: Choose if all of the response data for all groups or factor levels is in the same column.
Response: Enter the column that contains the response data.
Factors: Enter the columns that identify the group or factor level for each row.
Response data are in a separate column for each factor level: Choose if the response data for each group or factor level is in a separate column.
Responses: Enter the columns that contain the response data.