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Statistical power refers to the probability to correctly reject a false null prediction or the probability to accurately accept the true alternative prediction. The concept of power emerged as a countermeasure to misuse of statistics in null hypothesis significance testing. The demonstration of the impact of increasing sample and the change in size of the effect can be represented using a set of curves that provide the ability to make more accurate estimations of the power of a given statistic.

Problems of Null Hypothesis Significance Testing

In most social-scientific investigation, the exact treatment effect remains difficult to quantify. A researcher may be able to deduce a prediction from theory that, for example, threat messages are more prone to incur persuasive boomerang (creating attitude change in the opposite ...

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