The Five-Step Procedure for Hypothesis Testing

The Five-Step Procedure for Hypothesis Testing

Step 1

State the null hypothesis – equating the population parameter to a specification. The null hypothesis is always one of status quo or no difference. We call the null hypothesis H0 (H sub zero). It is the hypothesis that contains an equality. State the alternate hypothesis – The alternate is represented as H1 or HA (H sub one or H sub A). The alternate hypothesis is the exact opposite of the null hypothesis and represents the conclusion supported if the null is rejected. The alternate will not contain an equal sign of the population parameter. Most of the time, researchers construct tests of hypothesis with the anticipation that the null hypothesis will be rejected.

Step 2

Select a level of significance (ά or alpha) which will be used when finding critical value(s).

The level you choose indicates how confident we wish to be when making the decision. For example, a .05 alpha level means that we are 95% sure of the reliability of our findings, but there is still a 5% chance of being wrong. The level of significance is set by the individual performing the test. Common significance levels are .01, .05, and .10. It is important to always state the chosen level of significance.

Step 3

Identify the test statistic – this is the formula you use given the data in the scenario. Simply put, the test statistic may be a Z statistic, a t statistic, or some other distribution. Selection of the correct test statistic will depend on the nature of the data being tested (sample size, whether the population standard deviation is known, whether the data is known to be normally distributed).

The sampling distribution of the test statistic is divided into two regions, a region of rejection called the critical region and the non-rejection region. The rejection region lies in the tails of the curve starting at the critical value of the test statistic. The test statistic is the value calculated by using the appropriate sampling...