Power of the Test

Definition

Power of the test refers to the probability of correctly rejecting the null hypothesis when it is false. It measures how likely we are to detect an effect if it truly exists.

Related terms

Sample Size: Increasing the sample size generally increases the power of a test because it provides more data to detect an effect.

Effect Size: Effect size measures the magnitude of the difference or relationship between variables. Larger effect sizes tend to result in higher power.

Type II Error: Type II error occurs when we fail to reject the null hypothesis even though it is false, leading to a false negative result. Power and Type II error are inversely related - as power increases, Type II error decreases.