What is the peeking problem in A/B testing, and how does it inflate false positive rates? What solutions exist for continuous monitoring?

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The peeking problem occurs when experimenters repeatedly check results during an A/B test and stop as soon as they see statistical significance. This practice dramatically inflates false positive rates beyond the nominal alpha level, leading to incorrect decisions.