Chapter 4 Questions
11-list the five steps of hypothesis testing and explain the procedure and logic of each.
Step 1: Restate the question as a Research Hypothesis and a Null Hypothesis about the populations (Aron, 2009).
We want to put this into clear terms with our population 1 in the first group stating what our opinion of the research is, why we are performing the research, and what we feel the outcome will be.
We then state a null hypothesis to make clear we understand there is an alternative. That is, our prediction may not be correct, there may be no effect. This is considered population 2.
Step 2: Determine the characteristics of the Comparison Distribution (Aron, 2009).
We want to determine if the null hypothesis is true, what is the situation that makes it so. We want to state that the population 1 is not the normal curve and population 2 is. If the null is true, they will both follow the normal curve. We will compare the two scores of the test to examine our results and to test the hypothesis and the null against one another.
Step 3: Determine the Cutoff Sample Score on the Comparison Distribution at which the Null Hypothesis should be rejected (Aron, 2009).
Before our initial test, we will determine a score of which our results will be compared. We need evidence to prove that our hypothesis is true and the null is not. The significance level is the probability of making a Type I error. This occurs when the decision supports the alternative hypothesis when the null is true. A Type II error is one that supports the null when the alternative is true.
This is termed the “cutoff sample score” or “critical value” (Aron, 2009).
Step 4: Determine your sample’s score on the Comparison distribution
When you have arrived at the results of your test, you figure the z score for your sample’s raw score based on the population mean and standard deviation