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A statistical test's power is the probability that the test procedure will result in statistical significance. Power is related to the sample size, the size of the type I (alpha) error, the actual size of the effect, and the size of experimental error. All of these must be considered in order to calculate statistical power.
As statistical significance is usually the desired outcome, planning and running a study to achieve a high power is of prime importance to the researcher. Because of the complexity of the calculations, the determination of the power is often ignored or only a casual attempt is made at its calculation by adopting some, so-called, "rule-of-thumb."
PASS Beats the Competition!
PASS performs power analysis and calculates sample sizes. Use it before you begin a study to calculate an appropriate sample size (it meets the requirements of government agencies that demand technical justification of the sample size you have used). Use it after a study to determine if your sample size was large enough.
PASS lets you solve for power, sample size, effect size, and alpha level. It automatically displays charts and graphs along with numeric tables and text summaries in a portable format that is cut and paste compatible with all word processors so you can easily include the results in your proposal.