What Power is
Power is a statistical concept that refers to the ability of a hypothesis test to correctly reject the null hypothesis. It is a measure of the test’s sensitivity and the likelihood that it will detect an effect when one exists.
Power is calculated using the following steps:
- State the null hypothesis and the alternative hypothesis
- Calculate the significance level (α) of the test
- Calculate the statistical power (1-β) of the test
- Select an appropriate sample size
- Calculate the effect size (δ)
- Calculate the critical value (zα)
- Calculate the power of the test (1-β) using the formula:
Power = P(Reject H0|H1 is true) = P(z > zα|H1 is true)
- Interpret the results of the test
Examples
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Power analysis is used to calculate the sample size required to detect a difference between two groups with a specified level of confidence.
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Power analysis is used to determine whether the sample size of an experiment is large enough to detect a difference between two or more means.
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Power analysis is used to determine the probability that a statistical test will reject the null hypothesis when the null hypothesis is false.
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Power analysis is used to determine the probability that a statistical test will detect an effect when an effect actually exists.