Stats and Cats Blog
Browse by topic →Statistics, data, and the cats who make us feel better about all of it.
Posts
Anecdote and Data
What personal experience can and cannot tell you. Anecdote is not worthless: it is a sample of one from an unknown distribution. The weight it deserves depends on what else is known.
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.
Florence Nightingale's Rose Diagrams
How Nightingale used polar area charts to make mortality data legible to people who would not read a table, and why the design choices were deliberate and effective.
How Charts Mislead Without Lying
Truncated axes, dual y-axes, cherry-picked time windows, and area encoding errors. What to look for before trusting a chart.
Law of Large Numbers vs. the Gambler's Fallacy
The law of large numbers is a theorem. The gambler's fallacy is a mistake. They sound related and are easy to confuse. They say opposite things.
The Multiple Comparisons Problem
Run enough tests at a 0.05 threshold and something will look significant by chance. What the family-wise error rate means, why it matters, and what to do about it.
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.
Simpson's Paradox: When Subgroups Disagree With the Aggregate
How a trend that holds within every subgroup can reverse when those groups are combined, and why the Berkeley admissions data remains the clearest illustration.
Statistical Power: Why Small Studies Often Find Nothing
Power is the probability of detecting an effect that actually exists. A study that finds nothing may simply have been too small to find anything. Here's what determines power and why it matters before collecting data.
Survivorship Bias: The Sample You're Not Seeing
When you study only the outcomes that made it through a filter, you are not studying outcomes. You are studying a selection process. The WWII plane problem and why it matters wherever data gets filtered.
Articles on probability distributions, statistical inference, and the concepts that undergraduate statistics courses introduce but don't always make time to explain well. The cats are load-bearing.