Statistics - P-Values versus Critical Values Essay

Statistics - P-Values versus Critical Values - Essay ExampleHowever, if the calculated value is less than the critical value, the worthless hypothesis is accepted and the alternative hypothesis is rejected. The advantage of this system is that it helps define the rejection region in name of the sample mean and therefore if the same experiment is repeated many times in the field, unmatched back draw the conclusion of the hypothesis test right then without having to make any another(prenominal) calculations (Statistics Glossary, paratrooper 22). The disadvantage of this method is that one is stuck with a fixed level for the test. The probability value or p-value method is a measure of how likely the sample results are, assuming the null hypothesis is true. Small p-values refer that the null hypothesis is unlikely to be true. The smaller the p-value, the more convincing is the rejection of the null hypothesis. The advantage of this method is that, by reporting the p-value one al lows the reader to decide if the result is signifi piece of asst or not (Statistics Glossary, para 26). For e.g., one might think that the 5% level of significance is good while the reader whitethorn prefer 2% level of significance. Therefore, the p-value allows the reader to draw their own conclusions. The disadvantage of this method is that one cant make quick conclusions based on just the sample values as can be done in the critical value method.