According to Aron, Aron, & Coups (2009), there are five steps in the process of hypothesis testing .
Step 1: Restate the question as a research hypothesis and a null hypothesis about the populations.
A research hypothesis is a statement about the predicted relation between the two populations. The null hypothesis is opposite of the research hypothesis. If one of the hypothesis is true, the other cannot be. If I were to research the health of children who eat fresh vegetables versus children in general. My reseach hypothesis would be “Children who eat fresh vegetables are healthier than those who don’t.” My two populations would be children who eat fresh vegetables (population 1) and children in general (population 2).
Step 2: Determine the characteristics of the comparison distribution.
The comparison distribution represents population situation if the null hypothesis is true. This is the distribution that you compare the score based on your sample’s results. In my fresh vegetable example, the null hypothesis would be “There is no difference in the health of children who eat fresh vegetables than those who don’t.” The comparison distribution os the distribution of population 2.
Step 3: Determine the cutoff sample score on the comparison distribution at which the null hypothesis should be rejected.
The cutoff sample score is the point if reached or exceeded by the sample score that you reject the null hypothesis. In this step, you set the z score at a score that would be unlikely if the null hypothesis is true. For example, the researchers testing the vegetable hypothesis may decide that if a result were less than 3% then they would reject the null hypothesis.
Step 4: Determine your sample’s score on the comparison distribution.
This is the point where the study is carried out and the actual results for the sample are obtained.
Step 5: Decide whether to reject the null hypothesis.
Compare the actual sample’s z score to the cut off z score....