Power of test depend on excepta.significance levelb.the reliability of the sample sizec.the effect sized.population size

The power of a statistical test is influenced by several factors, including:

a. Significance level: The significance level, also known as the alpha level, is the probability of rejecting the null hypothesis when it is true. A lower significance level means a lower chance of making a Type I error (false positive), but it also reduces the power of the test.

b. The reliability of the sample size: The larger the sample size, the more reliable the results and the greater the power of the test. A larger sample size reduces the margin of error and the impact of random variation.

c. The effect size: The effect size is a measure of the strength of the relationship between two variables in the population. The larger the effect size, the greater the power of the test.

d. Population size: Contrary to what one might think, the power of a test does not depend on the population size. This is because statistical tests are based on the sample data, not the entire population. Therefore, the power of a test is not affected by the population size.