A statistical calculation that determines the probability of detecting an effect of a given size if it truly exists, or helps determine the sample size needed to detect an effect. Power is the ability to avoid Type II errors.
The concept of statistical power was developed by Neyman and Pearson in the 1930s, with Jacob Cohen's 1988 book making power analysis accessible to behavioral researchers. 'Power' metaphorically represents the strength or ability to detect true effects.
Power analysis is like choosing the right prescription for statistical glasses—it tells you how big your sample needs to be to actually see the effect you're looking for! Most psychology studies are underpowered, like trying to read fine print with weak glasses.
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