About Stats & Cats

Statistics is one of those subjects where the gap between "knowing the formula" and "understanding what it means" is enormous. Most explanations land somewhere in between — rigorous enough to be intimidating, informal enough to be imprecise — and people walk away with the right answer to the wrong question.

Stats & Cats is an attempt at something more useful: clear explanations of statistical concepts, written for people making real decisions. The blog covers probability, data interpretation, common analytical mistakes, and the mechanics behind numbers that show up in everyday life. Tools on the site are built for the same purpose — to make quantitative reasoning more accessible without dumbing it down.

The cats are there because statistics benefits from a good illustration, and cats are inherently more interesting than bar charts alone.

What gets covered

The writing focuses on statistical concepts that are frequently misunderstood or misapplied: p-values, confidence intervals, base rates, Simpson's paradox, correlation versus causation, and the ways that good data can produce misleading conclusions. Occasionally it covers tools, datasets, and techniques worth knowing about.

A note on rigor

The goal is clarity, not oversimplification. Where there's a meaningful distinction to make, the writing makes it. Where the intuition is close enough to be useful, it says so. Nothing here is meant to replace a statistics textbook — it's meant to make the textbook make more sense when you go back to it.