Harnessing Statistical Power for Test Results You Can Trust
ConversionXL
FEBRUARY 5, 2019
If your test is underpowered, you have an unacceptably high risk of failing to reject a false null. A Type I error, or false positive, rejects a null hypothesis that is actually true. A Type II error, or false negative , is a failure to reject a null hypothesis that is actually false. Type I and Type II errors. Type I errors.
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