Large Sample Effect

Posted in Statistics, Total Reads: 623
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Definition: Large Sample Effect

The power of a statistical test is basically the probability that a test would reject the null hypothesis when the null hypothesis is false. Therefore, the power reflects the probability of not making a type II error. The two major factors that affect the power of a study are the sample size and the effect size. Sample size and effect size are inversely related.


A study which has a sample size that is too small may produce inconclusive results. Similarly, a study that has a sample size which is too large will incur wastage of scarce resources and could expose more subjects than necessary to any related risk. Thus an appropriate estimation of the sample size used in a study is a crucial pointer in the design of a study.


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