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GCSE Maths · EdexcelChapter 23 · Probability
GCSE Maths · Probability · Foundation · Summary

GCSE Maths Probability (Foundation): summary and key words

Part of the GCSE Maths probability chapter (Foundation). Chapter overview · Higher version of this lesson · whole chapter on one page

Chapter summary

SkillMethod
Probability of an eventfavourable outcomes ÷ total outcomes, for equally likely outcomes. Always between 0 and 1.
Probability of not AP(not A) = 1 − P(A). All the probabilities of the outcomes add up to 1.
Relative frequencyfrequency ÷ number of trials. It estimates the probability. More trials give a better estimate.
Expected numberprobability × number of trials
Fair or biased?Compare relative frequencies with the theoretical probability, using plenty of trials. Fair does not mean exactly equal.
Listing outcomesList systematically or use a sample-space table. Probability = matching cells ÷ all cells (two dice: 36).
Counting outcomesProduct rule: multiply the number of choices at each stage.
Independent eventsP(A and B) = P(A) × P(B). “And” means multiply.
Mutually exclusive eventsP(A or B) = P(A) + P(B). “Or” means add.
At least oneP(at least one) = 1 − P(none)
Tree diagramsMultiply along the branches, add the routes. Without replacement the numbers on the second branches change.
Sets and Venn diagrams∩ both, ∪ either, A′ not in A, ξ everything. Fill in from the middle outwards. P = n(event) ÷ n(ξ).
Two-way tablesRows and columns add up to their totals. Probability = number ÷ grand total.
Frequency treesNumbers, not probabilities. Take a fraction of the number in the box before it.
Higher: P(A or B)P(A ∪ B) = P(A) + P(B) − P(A ∩ B)
Higher: conditional probabilityP(A | B) = P(A and B) ÷ P(B) = n(A ∩ B) ÷ n(B). “Given” shrinks the sample space.
Higher: probability and algebraWrite each probability with the unknown, form an equation (probabilities add to 1, or a route probability equals a given value) and solve.

Can you…?

  • I can use the words impossible, unlikely, even chance, likely and certain, and the probability scale from 0 to 1.
  • I can work out the probability of a single event when outcomes are equally likely.
  • I can use P(not A) = 1 − P(A) and find a missing probability.
  • I can work out a relative frequency and use it to estimate a probability.
  • I can find an expected number of outcomes.
  • I can say whether an experiment suggests a die or coin is fair or biased, and explain why more trials are better.
  • I can list outcomes systematically and use a sample-space table.
  • I can use the product rule to count outcomes.
  • I can use the AND rule for independent events and the OR rule for mutually exclusive events.
  • I can draw and use tree diagrams with and without replacement.
  • I can use set notation and Venn diagrams to count and to find probabilities.
  • I can complete and use two-way tables and frequency trees.
  • Higher: I can find conditional probabilities from tables, Venn diagrams and tree diagrams.
  • Higher: I can form and solve equations from probability information.

Key terms

Probability
A number from 0 to 1 that measures how likely an event is.
Outcome
One possible result of an experiment.
Event
An outcome or group of outcomes we are interested in.
Equally likely
Outcomes that each have the same chance of happening.
Random
Not predictable or rigged: each outcome has its fair chance.
Biased
Not fair: some outcomes are more likely than they should be.
Theoretical probability
Probability worked out from equally likely outcomes: favourable ÷ total.
Trial
One go of an experiment.
Frequency
The number of times an event happens.
Relative frequency
Frequency divided by the number of trials: an estimate of probability.
Expected number
Probability multiplied by the number of trials.
Complement
The event “A does not happen”, written not A or A′.
Exhaustive
Covering every possible outcome, so the probabilities add up to 1.
Mutually exclusive
Events that cannot happen at the same time.
Independent
Events where one has no effect on the probability of the other.
Dependent
Events where the result of one changes the probability of the other.
Sample space
The list or table of all possible outcomes.
Product rule for counting
Number of outcomes = (choices at stage 1) × (choices at stage 2) × ...
Tree diagram
A diagram of branches showing the outcomes of events in order, with their probabilities.
With replacement
An item is put back after it is picked, so probabilities stay the same.
Without replacement
An item is not put back, so later probabilities change.
Set
A collection of items called elements, written in curly brackets.
Universal set (ξ)
The set of everything being considered.
Intersection (A ∩ B)
The elements in both A and B.
Union (A ∪ B)
The elements in A or B or both.
Venn diagram
A diagram that uses overlapping circles inside a rectangle to show sets.
Two-way table
A table showing two categories at once, with row and column totals.
Frequency tree
A tree showing numbers of people or items instead of probabilities.
Conditional probability
The probability of an event given that another event has happened: P(A | B).

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