All null hypothesis statistical significance test (NHST) procedures follow eight steps: (1) forming groups in the data, (2) define the null hypothesis (H0), (3) set alpha (α), (4) choose a one-tailed or a two-tailed test, (5), calculate the observed value, (6) find the critical value, (7), compare the observed value and the critical value, and (8) calculate an effect size. For a z-test the effect size is Cohen’s d. This can be interpreted as the number of standard deviations between the two means.
A z-test is the simplest NHST and tests the H0 that a sample’s dependent variable mean and a population’s dependent variable mean are equal. If H0 is retained, then the difference between means is no greater than what would be expected from sampling error. If the H0 is rejected, it is not a good statistical model for the data.
When conducting NHSTs, it is possible to make the wrong decision about the H0. A Type I error occurs when a person rejects a H0 that is actually true. A Type II error occurs when a person retains a H0 that is actually false. It is impossible to know whether a correct decision has been made or not.
Review the options below to login to check your access.
Log in with your Cambridge Higher Education account to check access.
If you believe you should have access to this content, please contact your institutional librarian or consult our FAQ page for further information about accessing our content.