Leo+DadMade for Leo
Data Science · Part B
Concept · 4 steps · NESA SC4-DA1-01

Scientific Models

The idea that sits quietly under all of science — a model is a simplified stand-in for something real, built to do a job. From "wait, a map isn't the real city?" all the way to picking the right model for a question and naming where it breaks. Four short steps, each with its own toy to play with.


1 Where it comes fromA model is a simplified stand-in for something real. Sit a real thing beside its model and toggle what it keeps and what it drops. 2 How to do itThe four kinds of model — physical, diagram, mathematical, computer — and how to match one to a purpose so you can explain and predict. 3 Where it gets trickyThe map is not the territory. Every model is wrong somewhere — Greenland looks huge, the atom isn't a tiny solar system. 4 Out in the wildThe models that run the world — weather, disease, engineering — and reaching for the right one when handed a real question.