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Sample Ratio Mismatch (SRM) Check

intermediate~10 min25 pts
📊 View Insights

Problem

Before trusting any A/B test result, an analyst must confirm the traffic split actually landed close to what was configured. Your experimentation platform was configured for a 50/50 control/treatment split. After two weeks you observe:

  • Control: 24,100 users
  • Treatment: 25,900 users

Run a chi-square goodness-of-fit test against the expected 50/50 allocation and flag a Sample Ratio Mismatch (SRM) if the p-value is below 0.01 (the stricter threshold conventionally used for SRM, since even a small allocation bug can silently invalidate every downstream metric).

Return a dict result with keys chi2_stat (rounded to 4 decimals), p_value (unrounded), and srm_detected (bool).

A/B TestingSRMChi-SquareExperiment Health
📊
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Python Editor

Run your code to see the result here.

Topfolio

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courses

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  • Data Analyst vs Data Engineer vs Data Scientist

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company

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