The traditional or classical method involves using the critical value to conclude the hypothesis testing. As a first step, a hypothesis is stated and expressed symbolically as follows. For the proportion, mean, or standard deviation of a population, the null and alternative hypotheses are expressed as follows. Further, a critical value is obtained for the chosen parameter in the hypotheses at a specific predetermined significance level α. For proportion, mean, or standard deviation, these critical values at α are the z, t, or chi-square values, respectively, which are calculated using the z, t, or chi-square distributions. The critical value is then plotted to demarcate the critical region in the probability distribution. Further, the test statistic is calculated using the sample data and plotted on the probability distribution curve. The null hypothesis is rejected when the test statistic value falls within the critical region. However, we fail to reject it when the test statistic falls outside the critical region.