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How we change what others think, feel, believe and do
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How we change what others think, feel, believe and do |
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Experimental Power
Explanations > Social Research > Statistical principles > Experimental Power Description | Example | Discussion | See also
DescriptionThe power of a test is the probability that it will detect an effect (assuming one exists). A 'powerful' test is thus more useful and preferable to an experiment that is less powerful. A Type 2 error is one where an effect that exists is not found. The probability of this is beta (b). The power is thus the ability of an experiment to avoid type 2 errors and can be calculated as: Power = (1 - b) ExampleThe probability of a a student who has passed a school test actually being incapable is calculated as 20%. The Power of the test, the chance of a passing student being capable, is thus 80%. DiscussionIt is possible to identify the size of the sample needed to reach a given power for any test, although this requires complex calculations. Statistical tools may do this for you. See also.
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