The process of testing hypotheses follows a simple four-step procedure. This process will be what we use for the remained of the textbook and course, and though the hypothesis and statistics we use will change, this process will not.
Step 1: State the Hypotheses
Your hypotheses are the first thing you need to lay out. Otherwise, there is nothing to test! You have to state the null hypothesis (which is what we test) and the research hypothesis (which is what we expect). These should be stated mathematically as they were presented above AND in words, explaining in normal English what each one means in terms of the research question.
Step 2: Find the Critical Values
Next, we formally lay out the criteria we will use to test our hypotheses. There are two pieces of information that inform our critical values: \(α\), which determines how much of the area under the curve composes our rejection region, and the directionality of the test, which determines where the region will be.
Step 3: Compute the Test Statistic
Once we have our hypotheses and the standards we use to test them, we can collect data and calculate our test statistic. This step is where the vast majority of differences in future chapters will arise: different tests used for different data are calculated in different ways, but the way we use and interpret them remains the same.
Step 4: Make the Decision
Finally, once we have our calculated test statistic, we can compare it to our critical value and decide whether we should reject or fail to reject the null hypothesis. When we do this, we must interpret the decision in relation to our research question, stating what we concluded, what we based our conclusion on, and the specific statistics we obtained.
We will talk more about what is included in the write-up that explains the interpretation of the decision in relation to the research question, but remember that your answer is never just a number in behavioral statistics. And in Null Hypothesis Significance Testing, your answer is probably at least several sentences explaining the groups, what was measured, the results. and how it all relates to the research hypothesis.