What this topic covers
Probability has 4 subtopics:
- Probability Foundations
- Sample Spaces and Systematic Enumeration
- Combined Events and Tree Diagrams
- Conditional Probability
IGCSE Edexcel Higher Maths · Topic 9 of 12
Choose a subtopic. Probability covers Probability Foundations, Sample Spaces and Systematic Enumeration, Combined Events and Tree Diagrams, and Conditional Probability in IGCSE Edexcel Higher Maths. 12 lessons in 4 subtopics.
Revise Probability for IGCSE Edexcel Higher Maths, including Probability Foundations and Sample Spaces and Systematic Enumeration.
12
Lessons
4
Subtopics
Probability has 4 subtopics:
12 lessons, grouped by subtopic.
Go back to the full IGCSE Edexcel Higher Maths topic list, or practise this topic with past-paper questions.
Probability covers Probability Foundations, Sample Spaces and Systematic Enumeration, Combined Events and Tree Diagrams, and Conditional Probability in IGCSE Edexcel Higher Maths. 12 lessons in 4 subtopics.
A sample space diagram is a two-way grid listing every outcome of two combined events, with one event across the top and the other down the side. The Systematic Enumeration Using Tables, Grids and Venn Diagrams notes cover this in full.
At GCSE level, the law of large numbers means that as the number of trials increases, the relative frequency gets closer to the theoretical probability. The Experimental Probability, Relative Frequency and Sample Size notes cover this in full.
Every probability is between 0 and 1: 0 means impossible, 1 means certain and 0.5 means an even chance. The Relative Frequency and Theoretical Probability notes cover this in full.
Divide the number of times an outcome occurs by the total number of trials. The Recording and Analysing Probability Experiments notes cover this in full.
The complement A′ is everything in the universal set ξ that is not in A, shown on a Venn diagram as everything outside circle A. The Systematic Enumeration Using Tables, Grids and Venn Diagrams notes cover this in full.
Exhaustive events are events that between them cover every possible outcome of an experiment, so one of them must happen. The Exhaustive Sets and Mutually Exclusive Events notes cover this in full.
For independent events, P(A and B) = P(A) × P(B), because P(B|A) = P(B). The Tree Diagrams for Combined Events notes cover this in full.
Conditional probability, written P(A | B), is the probability of event A occurring given that event B has already occurred. The Conditional Probability from Tables, Tree Diagrams and Venn Diagrams notes cover this in full.