## When would one want to use a post hoc test is it necessary to run a post hoc test if the results of an ANOVA are not significant Why or why not?

Because post hoc tests are run to confirm where the differences occurred between groups, they should only be run when you have a shown an overall statistically significant difference in group means (i.e., a statistically significant one-way ANOVA result).

## When would you use Ancova instead of ANOVA?

ANOVA is used to compare and contrast the means of two or more populations. ANCOVA is used to compare one variable in two or more populations while considering other variables.

**What are post hoc tests and when should they be used?**

A post hoc test is used only after we find a statistically significant result and need to determine where our differences truly came from. The term “post hoc” comes from the Latin for “after the event”. There are many different post hoc tests that have been developed, and most of them will give us similar answers.

**What if my post hoc test is not significant?**

Yes dear it is possible to get insignificant result after ANOVA. Because post hoc tests are run to confirm where the differences occurred between groups, they should only be run when you have a shown an overall significant difference in group means (i.e., a significant one-way ANOVA result).

### What does post hoc mean in statistics?

In a scientific study, post hoc analysis (from Latin post hoc, “after this”) consists of statistical analyses that were specified after the data were seen. This typically creates a multiple testing problem because each potential analysis is effectively a statistical test.

### What is an example of a post hoc test?

The most common post hoc tests are: Bonferroni Procedure. Duncan’s new multiple range test (MRT) Dunn’s Multiple Comparison Test.

**What does it mean if ANOVA is significant but post hoc is not?**

Post hoc tests are an integral part of ANOVA. When you use ANOVA to test the equality of at least three group means, statistically significant results indicate that not all of the group means are equal. However, ANOVA results do not identify which particular differences between pairs of means are significant.