Scenario
You are a data scientist presenting A/B test results to non-technical executives who must decide whether to launch a product change.
Question
In plain language:
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What is a p-value?
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Why is it important when making product decisions?
Hints
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Think: "Probability of seeing results at least this extreme if the change actually had no real effect."
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Connect to the risk of false positives (shipping a change that doesn’t truly help).