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DataScience Post #4931 · source on Telegram

Ignoring causation caveats, entire dev team samples “yummy fruit” with fatal results

Description

Four-panel stick-figure comic with simple black line art and bright magenta ovals on a white background. Panel 1 (top-left) shows a crowd of smiling stick people gathered around several magenta ovals on the ground; one happy figure holds an oval to its mouth while the caption above reads “yummy fruit”. Panel 2 (top-right) depicts the same crowd now frowning as one figure lies on the ground with Xs for eyes next to the magenta ovals. Panel 3 (bottom-left) has the crowd smiling again while one points to the scene and the caption “correlation does not equal causation” appears overhead - even though the corpse is still present. Panel 4 (bottom-right) shows multiple stick figures now dead, sprawled among more magenta ovals. The meme satirizes the common statistical warning that correlation alone cannot prove causation; by ignoring that principle, everyone continues the experiment and suffers catastrophic ‘production’ failure - an analogy familiar to data scientists and engineers who rely on A/B testing, causal inference, and post-incident learning

Comments

6
Anonymous ★ Top Pick Canary cohort drops to zero, p-value is 0.06; Product says “statistically insignificant - roll to 100%.” SRE adds a new KPI: users_alive p95
  1. Anonymous ★ Top Pick

    Canary cohort drops to zero, p-value is 0.06; Product says “statistically insignificant - roll to 100%.” SRE adds a new KPI: users_alive p95

  2. Anonymous

    After analyzing our A/B test results for three months, we finally discovered the purple fruit feature wasn't driving user retention - it just happened to be the only thing left after everyone who could quit already did

  3. Anonymous

    This is every ML engineer's nightmare when stakeholders see two trending lines and immediately demand a predictive model - only to discover later that both metrics were actually driven by a third variable no one thought to instrument. It's the data science equivalent of debugging for hours only to find the real issue was a completely different service that nobody mentioned in the incident channel

  4. Anonymous

    A/B test shows 300% engagement lift from new button color - causation? Nah, just uncontrolled for pizza Fridays

  5. Anonymous

    Enterprise causal inference: if correlation threatens the roadmap, the HIPPO declares it not causation, cancels the RCT, and ships - postmortem-ready

  6. Anonymous

    A/B test shows the treatment cohort keeps dying; PM: “correlation ≠ causation.” SRE: “Perfect - let’s ramp to 100% and establish causality.”

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