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Power: The probability that you would identify a true effect of the independent variable. Type Two error: Labeling an outcome as related to random events when it actually is because of the independent variable. Type Two error: Accepting the null hypothesis when it is false. error Where represents the probability that this type of error would occur. Ho : = 50 H1: > 50 = .05 50 o 0 1 Power = 1 - 0 1 Three things can effect power. 1) The level of significance gets smaller gets bigger 2) Increase the sample size (N) Larger N - smaller standard error Therefore less overlap of the distributions 3) Increase the distance from 0 to 1 0 1