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Articles tagged with featured in Stats and Cats.

  • The Central Limit Theorem: Why Averages Behave

    Individual observations can follow nearly any distribution. Average enough of them together, and the result converges toward normal. Here's why that happens and why it matters.

  • Regression to the Mean: Why Exceptional Performance Doesn't Last

    Extreme outcomes tend to be followed by more ordinary ones. This is not a psychological phenomenon. It is a mathematical one, with real implications for how we evaluate causes and interventions.

  • What Confidence Intervals Actually Tell You

    A 95% confidence interval does not mean a 95% probability that the true value is inside it. Here is what the statement actually means, and why the distinction is worth getting right.

  • The Base Rate Fallacy: When a Positive Test Isn't Good Evidence

    A 99% accurate test for a rare condition still leaves you more likely than not to be healthy after a positive result. Bayes' theorem explains why the prior matters.

  • Correlation Is Not Causation, Illustrated With Cat Food

    A study shows premium cat food extends feline life. It probably doesn't. A walkthrough of confounders, causal DAGs, and collider bias: the machinery behind each illusion.

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