How can a researcher make a non-parametric test more powerful (less likely to miss a true relationship between variables)?
A) Use a more rigorous rejection level such as .01 or .005.
B) Use a larger research sample.
C) Select the rejection region only after the results of the test are known.
D) all of the above

Question

Quizplus · Accepted Answer

Increasing the sample size will increase the power of a non-parametric test by reducing the standard error of the mean and increasing the likelihood of detecting a true relationship between variables. Using a more rigorous rejection level or selecting the rejection region only after the results of the test are known may increase the likelihood of a type I error, which could lead to false positives or rejecting the null hypothesis when it is actually true.

How Can a Researcher Make a Non-Parametric Test More Powerful