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Relationship Between Statistical Power and Type II Error
Statistical power and the probability of committing a Type II error are perfectly complementary. A Type II error occurs when a researcher fails to reject a false null hypothesis (missing a real effect). Since statistical power is the probability of correctly rejecting that false null hypothesis, statistical power is calculated as . Therefore, maximizing a study's statistical power is the primary method for minimizing the risk of making a Type II error.
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Research Methods in Psychology - 4th American Edition @ KPU
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Which of the following best defines the statistical power of a research design?
A researcher designs a study with a statistical power of .80. This means there is a 20% probability that the study will fail to detect a real effect that actually exists in the population.
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A psychology researcher wants to reduce the chance of failing to detect a real effect in a study. Given that statistical power is complementary to Type II error, what should the researcher do?
Because statistical power and the probability of a Type II error are complementary, designing a study with higher statistical power reduces the chance of failing to detect a real effect.