causal-claim-check

Pressure-test a claim that one thing caused another before anyone acts on it. Always use this skill when someone asks whether X causes or drives Y, whether a correlation is causal or just confounding, whether a change, campaign, feature or policy really worked, what to control for when estimating an effect, whether an observational result can be trusted as a causal effect, whether an estimate was biased because the effect shrank or grew after adding a control, when an experiment is needed instead of regression with controls, or whether the groups being compared were alike to begin with, even when the question sounds like a simple yes or no. Also use it for selection bias, confounders and omitted variable bias. Not for designing or reading a randomised A/B test, not for reading the coefficients of a prediction model, and not for checking regression assumptions.