Modelling unpredictable events. Sample spaces, events, conditional probability, Bayes' theorem — the formal language for reasoning about chance.
Volume 6 — Probability and data
Volume 6
Probability and Data
Often you won't have the exact formula or the complete set of facts. This volume provides the tools for operating in those grey areas where outcomes are determined by chance or obscured by noise.
By the end you will be able to formally measure the likelihood of future events, recognise the natural shapes that variation takes, draw robust conclusions from limited samples, and separate real signals from random fluctuations.
4 chapters
Grade 11–12
Needs Volumes 4–5
Chapter Map
Recognising shapes of variation. Binomial, Poisson, and Normal distributions — the recurring patterns that appear wherever random quantities accumulate.
Drawing conclusions from valid samples. Confidence intervals, hypothesis tests, and why a result being unlikely under chance is not the same as it being meaningful.
Finding signals in noise. Regression, correlation, and exploratory techniques — the practical workflow from raw numbers to defensible conclusions.