Question

explain the difference between statistical significance and practical significance. choose the correct answer below. a. statistical significance refers to how an unusual event is unlikely to actually appear in a real world application, such as every entry in a sample of size 50 having the same value. practical significance refers to how an unusual event is likely to actually appear in a real world application, such as a rejection of a null hypothesis using data that looks feasible. b. statistical significance means that the hypothesis test being performed is useful for building theoretical foundations for other statistical work. practical significance means that the particular application of the hypothesis test is of great importance to the real world. c. statistical significance means that the sample statistic is not likely to come from the population whose parameter is stated in the null hypothesis. practical significance refers to whether the difference between the sample statistic and the parameter stated in the null hypothesis is large enough to be considered important in an application. d. statistical significance refers to the type of hypothesis test needed to analyze a population, with some tests being more important than z tests. practical significance refers to how difficult a desired hypothesis test is to perform in an application, with some tests being easier to perform than others.

Explanation:

Statistical significance is about the unlikelihood of a sample statistic coming from the null - hypothesis population (based on probability in hypothesis testing). Practical significance is about whether the difference between the sample statistic and the null - hypothesis parameter is large enough to matter in a real - world application.

Answer:

C. Statistical significance means that the sample statistic is not likely to come from the population whose parameter is stated in the null hypothesis. Practical significance refers to whether the difference between the sample statistic and the parameter stated in the null hypothesis is large enough to be considered important in an application.