Increasing sample size is often the easiest way to boost the statistical power of a test.
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They introduced the concepts of " Type II " error, power of a test and confidence intervals.
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The statistical power of a test is the probability that it correctly rejects the null hypothesis when the null hypothesis is false.
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This is closely related to probably approximately correct ( PAC ) learning, where the learner is evaluated on its predictive power of a test set.
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Egon Pearson ( Karl's son ) and Jerzy Neyman introduced the concepts of " Type II " error, power of a test and confidence intervals.
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One easy way to increase the power of a test is to carry out a less conservative test by using a larger significance criterion, for example 0.10 instead of 0.05.
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