I would like help on responding back to these two discussion questions.

I am unsure on how to respond back to the statement's made.

Question: What is a post-hoc test and why it is necessary when rejecting the null hypothesis with an analysis of variance (ANOVA) statistical test? Describe what a post hoc test detects. Explain an experiment in which you as a researcher would run a post hoc test. Why?

Danny said: "Since the ANOVA test are testing the hypotheses against multiple factors, there can be more than one treatment groups with a significant mean difference. The purpose of the post hoc test is to determine if multiple sample mean differences are large enough to be considered significant. A post hoc test essentially allows you to go back through the data gathered and compare individual treatments two at a time. This process is known as pairwise comparisons. An example of this would be comparing different brands of basketballs and determining if there is a performance difference in the way a player shoots. A null hypothesis can be stated using the standard NBA issued basketball. Five other brands of basketballs can be compared against the hypothesis to determine if there is a significant difference from the mean."

(What could I respond back to him with?)

Ramiah said: "Post hoc testsare additional hypothesis tests that are done after an ANOVA to determine exactly which mean differences are significant and which are not. They are necessary when rejecting the null hypothesis with an ANOVA test because they because they point to exactly which means are significantly different. The post hoc test detects exactly where the mean differences lie for example if we were doing a study on which medical treatment out of 3 medications was best for treating ADHD and we discover that there was a M1 = 5, M2 = 7, and M3 = 10 we would know that there is a significant difference and we would run the post hoc test to see where the biggest difference lies.

(What could I respond back to her with?)