Data & Statistics Literacy

The headline says the risk has doubled. Doubled from what? If it rose from one in a million to two in a million, the sentence is arithmetically true and practically empty — yet it reads exactly like a warning worth reorganising your life around. Numbers reach you every day pre-packaged like this: a survey "proves", a chart soars, a treatment "works in 90% of cases". This track is about unwrapping the package before you believe what is inside.

Five step-by-step modules, and nothing beyond everyday arithmetic. You start with the oldest trap of all — things that move together without one causing the other, and the hidden third factors that fool even careful people. Then you see what it actually takes to know something works: a fair experiment, built piece by piece, the same A/B machinery behind every "which version is better?" decision in tech and medicine. The middle module is a tour of the probability traps your own intuition sets for you — including why a positive result from a 99%-accurate test usually does not mean what you think. The last two turn to the numbers in the wild: which average you are being shown and why it was chosen, when a sample can speak for a population, and finally how to pass uncertainty on honestly when it is your turn to write the sentence.

There is deliberately no machinery here — no formulas to memorise, no model to fit — because the skill being trained is judgement, not calculation. It is the doorway track of the whole statistics pillar: teachers, translators, journalists and managers can walk in cold, and readers heading for the technical tracks will find that ten minutes of trap-spotting here saves hours of confusion later. When a claim starts to smell wrong and you want the tools to prove it, Statistics Core is next door.