The sum of squares and degree of freedom calculation from the previous videos are put into a ratio to calculate the F Value, on whose basis the null hypothesis is confirmed or rejected. If variance is higher between samples than within the null hypothesis is more likely to be rejected. The results of a numerical example are interpreted more abstractly and then tested with regards to a confidence interval and the corresponding F table.

The chi-square distribution is used to test a hypothesis. Therefore, expected values are related to observed values using a chi-square distribution. Then using p-value tables the hypothesis is tested at a 5% significance level.