Statistical Significance: Is Your Result Real or Just Random?
Statistical significance checks if a result is a real effect or just random chance. It answers: 'How surprising is this data if my change had no effect?' It's used in A/B tests to validate new features. The footgun: a significant result isn't always important.
Statistical significance is a formal check to see if your result is a genuine effect or just random noise. It answers: 'Assuming my change did nothing (the null hypothesis), what's the probability I'd see a result this extreme by chance?' This is the core of A/B testing, confirming a new feature actually improved a metric. The biggest footgun is equating statistical significance with practical importance. With a massive sample size, a tiny, useless effect can be statistically significant but irrelevant to the business.
Read the original → Wikipedia: Statistical significance
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- #a/b testing
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- #hypothesis testing
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