Expected value often feels especially misleading when students apply it to small experiments. After calculating an expected value, students naturally expect results to align with it fairly quickly. When outcomes differ — sometimes dramatically — confidence drops, and students begin to doubt the concept itself.
The key issue is scale. Expected value describes what happens on average over a very large number of trials. Small experiments simply do not provide enough repetitions for that average to stabilise. Random variation dominates early outcomes, which means results can look nothing like the expected value at first.
Students struggle with this because earlier maths trains them to trust averages immediately. In statistics and probability, averages behave differently. A small number of trials does not “smooth out” randomness. Instead, extreme results have a much larger influence, making outcomes volatile and unpredictable.
Another reason expected value feels misleading is emotional. When an experiment involves gains, losses, or scores, students attach meaning to individual outcomes. Losing repeatedly despite a positive expected value feels unfair, even though it is mathematically normal. IB expects students to recognise this emotional response and separate it from statistical reasoning.
Expected value also hides variability. Two experiments can have the same expected value but very different spreads. In small samples, that spread matters more than the average. Students who focus only on expected value miss this nuance and overestimate its predictive power.
IB examiners deliberately test this misunderstanding. Questions often ask students to comment on whether expected value is a reliable guide in a given situation. Students who mention small sample size, randomness, and variability consistently earn higher marks than those who simply restate the expected value.
This is also why IB discourages strong conclusions based solely on expected value. Saying an option is “better” without mentioning uncertainty often loses interpretation marks. Expected value supports decisions, but it does not remove risk.
Once students accept that expected value is weak in the short term and strong in the long term, the confusion disappears. The concept stops feeling misleading and starts feeling realistic.
Frequently Asked Questions
Is expected value useless in small experiments?
No, but it should be treated cautiously. It gives long-term guidance, not short-term predictions.
Why does IB still use small-sample questions?
To test interpretation, judgement, and understanding of limitations.
What wording earns marks in these questions?
References to randomness, small sample size, and unreliable short-term outcomes.
RevisionDojo Call to Action
Expected value only misleads when it’s overtrusted. RevisionDojo is the best platform for IB Maths AI because it trains students to interpret expected value realistically and explain its limits clearly. If expected value questions feel confusing or unfair, RevisionDojo helps you turn them into consistent marks.
