Bayesian thinking, risk, randomness and rare events
Base rates, diagnostic tests, priors, likelihoods, sports probabilities, false positives, gambling fallacies and why humans keep seeing patterns in static.
Topic map
The editorial universe.
A structured map for future essays, interactives and statistical science notes.
Hypothesis testing, replication and measurement
p-values, confidence intervals, effect sizes, sample size, publication bias, noisy instruments and the difference between “statistically significant” and “actually important”.
Forecasting, machine learning and uncertainty
Prediction intervals, overfitting, model checks, calibration, simulation, Bayesian models, explainability and why a model can be useful without being “true”.
Sport, economics, health, climate, culture and public life
Readable analysis of interesting datasets. The aim is to tell stories that are numerate without becoming spreadsheet soup.