Determine the sample size and run time an experiment needs to detect a real effect without fooling yourself.
## CONTEXT Underpowered experiments are worse than no experiments because they produce confident-looking conclusions that are actually noise, so deciding up front how much data is needed to detect an effect worth caring about is the most important and most skipped step in the entire process. A team keeps running tests…
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