Question

Why is the omnibus F test considered a gate keeper? What should you do if your F value is significant? What should you do if your F test is not significant?

Answer 1

The omnibus F test is a statistical test procedure to see whether the explained variance in a set of data is significantly greater than the unexplained variance, overall. One example is the F-test in the analysis of variance. There can be legitimate significant effects within a model even if the omnibus test is not significant. For instance, in a model with two independent variables, if only one variable exerts a significant effect on the dependent variable and the other does not, then the omnibus test may be non-significant. This fact does not affect the conclusions that may be drawn from the one significant variable. In order to test effects within an omnibus test, researchers often use contrasts. It is considered a gate keeper because it allows for testing the hypothesis that tends to find general significance between parameters' variance, while examining parameters of the same type.

If the F-value is significant then we reject the null hypothesis at level of significance. That is we accept the alternative hypothesis which considers that at least two of the parameters are not equal.

If the F- value is not significant we simply accept the null hypothesis that parameters do not differ significantly at level of significance.