XIII. Testing Means


David M. Lane


Significance Testing, Type I and Type II Errors, Misconceptions

Learning Objectives
  1. Define power
  2. Identify situations in which it is important to estimate power

Power is defined as the probability of correctly rejecting a false null hypothesis. In terms of our example, it is the probability that given there is a difference between the population means of the new method and the standard method, the sample means will be significantly different. The probability of failing to reject a false null hypothesis is often referred to as β. Therefore power can be defined as:

power = 1 - β.

It is very important to consider power while designing an experiment. You should avoid spending a lot of time and/or money on an experiment that has little chance of finding a significant effect.

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