Hypothesis Testing

Qualitative Results
Quantitative Results

Hypothesis testing is a scientific process of testing whether or not the hypothesis is plausible.  The following steps are involved in hypothesis testing:

The first step is to state the null and alternative hypothesis clearly. In hypothesis testing, you can use either a one-tailed or two-tailed test for the null and alternative hypotheses.

The second step is to determine the test size. This means that the researcher decides whether to use a one-tailed or two-tailed test in order to obtain the correct critical value and define the rejection region.

The third step is to compute the test statistic and the probability value. This step of the hypothesis testing also involves the construction of the confidence interval depending upon the testing approach.

The fourth step involves the decision making step. This step of hypothesis testing helps the researcher reject or accept the null hypothesis by making comparisons between the subjective criterion from the second step and the objective test statistic or the probability value from the third step.

The fifth step is to draw a conclusion about the data and interpret the results obtained from the data.

There are basically three approaches to hypothesis testing. The researcher should note that all three approaches require different subject criteria and objective statistics, but all three approaches give the same conclusion.

The first approach is to test the statistic approach.

The common steps in all three approaches of hypothesis testing is the first step, which is to state the null and alternative hypothesis.

The second step of the test statistic approach is to determine the test size and to obtain the critical value.  The third step is to compute the test statistic. The fourth step is to reject or accept the null hypothesis depending upon the comparison between the tabulated value and the calculated value.  If the tabulated value in hypothesis testing is more than the calculated value, than the null hypothesis is accepted.  Otherwise it is rejected. The last step of this approach of hypothesis testing is to make a substantive interpretation.

The second approach to hypothesis testing is the probability value approach. First, determine the test size. Then, compute the test statistic and probability value. Reject the null hypothesis if the probability value is less than the tabulated value. Finally, make a substantive interpretation.

The third approach is the confidence interval approach. First, determine the test size or (1 – test size) and the hypothesized value. Then, construct the confidence interval. Reject the null hypothesis if the hypothesized value falls outside the interval. Finally, make a substantive interpretation.

The first approach to hypothesis testing is the classical test statistic approach. It computes a test statistic from the data and compares it to the critical value. If the test statistic exceeds the critical value, the researcher rejects the null hypothesis. Otherwise, the researcher accepts the null hypothesis.