Chance helps us reason when outcomes vary. It asks what can be predicted, what remains uncertain and how evidence should change our expectations.
Uncertainty is not a failure of mathematics. It is the thing mathematics is helping you describe.
What can we know when outcomes are uncertain?
Chance helps us reason when outcomes vary. It asks what can be predicted, what remains uncertain and how evidence should change our expectations.
Uncertainty is not a failure of mathematics. It is the thing mathematics is helping you describe.
Flip a coin ten times, or imagine ten flips.
Would exactly five heads surprise you? Would eight? What would change if you repeated the experiment many times?
Notice 1
What outcomes are possible?
Notice 2
Which outcomes feel likely, and why?
Notice 3
How does a sample differ from the long-run pattern?
Notice 4
What evidence would change your mind?
Explore how simple local rules create order, randomness and emergent patterns.
ExplorationBuild two-stage tree diagrams and compare replacement with no replacement.
ToolCompare training error, test error and model complexity.
Tool and explorationEstimate pi and area under a curve using random sampling.
Tool and explorationSee rejection regions, z statistics, p-values and conclusions.
ToolExplore binomial distributions, sampling and sample means.
ToolExplore G(n, p), connected components and random network behaviour.
ExplorationCompare plurality, Borda count, instant runoff and head-to-head fairness.
ExplorationTree diagrams, distributions, sampling and hypothesis tests all turn uncertainty into something we can reason about.
Probability often depends on combining chances, proportions and repeated trials.