Explain how the power of a hypothesis test is influenced by each of the following. Assume that all other factors are held constant.

Explain how the power of a hypothesis test is influenced by each of the following. Assume that all other factors are held constant.

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August 20, 2021
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Explain how the power of a hypothesis test is influenced by each of the following. Assume that all other factors are held constant.
a. Increasing the alpha level from .01 to .05.

b. Changing from a one-tailed test to a two-tailed test.

Answer and ExplanationSolution by a verified expert

a
Explanation
The power of the hypothesis refers to the likelihood of accurately refusing to accept the false null hypothesis by testing and knowing the probability that the treatment effect really exists or not. There are factors that affecting the power such as the sample size and whether it is one-tailed or two-tailed. There is also a direct relationship between treatment and power. When the size of the treatment magnitude increases, the power also increases. When the researcher chose the alpha level that increasing its value, the more chance of imprecisely rejecting the null hypothesis and reducing the potential of the confidence level.

b
Explanation
The power of a hypothesis test can indeed be influenced by changing from a one-tailed test to a two-tailed test. This is mainly because if the test is one-tailed, it is considered more powerful than a two-tailed one and a person is less likely to miss a statistically significant test result if the predicted direction is accurate. Seeing that one-tailed tests can test effects only in one direction, and it has no absolute capacity to detect an effect in the other direction. Altering from a one-tailed test to a two-tailed test, increases the ability to detect positive and negative effects of test results as it allows to test on those two directions. Allowing for an extension of the ability to detect or discover any type of effects in scientific researches in particular. The use of either one-tailed tests or two-tailed tests, can differ on the data set or hypothesis that you aim to statistically analyze, proper knowledge on both of these tests can help us be better equipped on what to use in specific circumstances.

Reference:

Frost, J. (n.d.). One-Tailed and Two-Tailed Hypothesis Tests Explained. https://statisticsbyjim.com/hypothesis-testing/one-tailed-two-tailed-hypothesis-tests/

Answer
The power of a hypothesis test can indeed be influenced by changing from a one-tailed test to a two-tailed test. This is mainly because if the test is one-tailed, it is considered more powerful than a two-tailed one and a person is less likely to miss a statistically significant test result if the predicted direction is accurate. Seeing that one-tailed tests can test effects only in one direction, and it has no absolute capacity to detect an effect in the other direction. Altering from a one-tailed test to a two-tailed test, increases the ability to detect positive and negative effects of test results as it allows to test on those two directions.

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