Describe in detail the differences in ANOVA and the five-step hypothesis testing method.
1. State hypothesis and alternate.
2. Level of significance
3. Identify test statistic
4. Formulate decision rule
5. Make the decision to accept or reject null hypothesis
To begin with, I will explain the fundamental difference between ANOVA and 5-step testing.
5-stop testing is also called t-testing. With t-testing you are seeing if a difference exists between 2 sample. I.e you want to know if a difference exists between 2 groups of students - one group of students study with music and the other group of students study in the quiet.
With an ANOVA, you are essentially testing the difference between many groups. Ie, you would want to see if a difference exists between 4 groups of students - one group of students study with music and the other group of students study in the quiet, a third studies in the library and the last group studies at home.
So the two techniques measure the same thing - differences between groups.
Why not use t-test for many groups? Well, it might be ok if there are three groups to compare - you would test group 1 against group 2 and group 1 against group 3, and group 2 against group 3. What if you had 10 groups? To compute individual t-tests would be time consuming and frustrating. ...
This solution provides a preface description, in detail, of the differences in ANOVA and the five-step hypothesis testing method. The expert then goes on to explain hypotheses and alternates, level of significance, identification of test statistics, formulation of decision rule, and then how to make a decision whether to accept or reject null hypotheses.