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Effect Size

In a hypothesis test, the power of the test refers to the probability that the test will reject the null hypothesis when the null hypothesis is false.

To compute the power of the test, one offers an alternative guess about the "true" value of the population parameter, assuming that the null hypothesis is false. That true value is called the critical value. The effect size is the difference between the critical value and the value specified in the null hypothesis.

For example, suppose the null hypothesis states that a population mean is equal to 100. A researcher might ask: What is the probability of rejecting the null hypothesis if the true population mean is equal to 90? In this example, the critical value would be 90. The effect size would be 90 - 100, which equals -10.

See also:   Statistics Tutorial: Power of a Hypothesis Test