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Effect Size

Effect Size:

In a study or experiment with two groups (usually control and treatment), the investigator typically has in mind the magnitude of the difference between the two groups that he or she wants to be able to detect in a hypothesis test. This magnitude, e.g. a 20% improvement in click-through rates, or a 20 point drop in blood pressure, is the effect size. Sample sizes are then chosen so that the probability of detecting this effect size, if it exists, is high. Too small a sample, and the effect may go unnoticed because it is not distinguishable from random variation. Too large a sample may guarantee detecting the effect, if it exists, but wastes resources.

See Sample Size Calculations.

Browse Other Glossary Entries

Courses Using This Term

Meta Analysis 1
This course will explain meta analysis and the methods that are used to assess multiple statistical studies on the same subject and draw conclusions.
Sample Size and Power Determination
This course will teach you how to make sample size determinations for various statistical tests and for confidence intervals, as needed for experimental studies such as comparison studies, as well as for other types of experiments.
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