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Comment on Deriving formulas for the expected sample size needed in A/B tests

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That looks right to me. This is a very important calculation to do in order to avoid getting 100x the number of samples that you really need.

Essentially the same calculation applies to classification error.

The real (and all to common to run into ) problem isn't having 100x the samples you really need, it is having 1/10 the samples you really need... And not knowing that.

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