Naked Statistics: Stripping the Dread from the Data
About this book
Wheelan explains the statistical ideas that turn up in ordinary working life without asking the reader to do much of the maths. Chapters cover descriptive statistics and what an average conceals, correlation, basic probability, the central limit theorem, inference, polling, and regression analysis with a clear warning about how it gets abused. The examples come from sport, medicine, education policy and business rather than from textbooks, and the tone sits closer to popular science than to a course. There is a useful chapter on how data gets collected badly and why that matters more than the analysis that follows. A reasonable first statistics book for anyone who reads dashboards for a living.
Description via Product Digest.
Topics
Related concepts
- Segmentation in analyticsCutting a population so an average stops describing nobody, the cuts that usually pay, and a worked case of Simpson's paradox where a signup rate improves on every device and the combined figure falls from 14.8 per cent to 12.9 per cent.
- Statistical significanceWhat a p value claims and what it cannot claim, what a confidence interval adds that a verdict of significant throws away, and why a difference can be statistically significant and still too small to fund.
- Sample size and statistical powerThe minimum detectable effect, statistical power and the relationship that ties them to the number of people a test needs, a table running from a one per cent improvement to a fifty per cent one with the arithmetic shown, and what follows honestly for a product with modest traffic.
- Evaluating a machine learning modelWhy accuracy is usually the wrong number, what precision and recall are really trading against each other, why the threshold is a product decision and the business metrics that decide whether any of it was worth doing.