Sample space and events
Sample space S: Set of ALL possible outcomes. Example: coin={H,T}. Die={1,2,3,4,5,6}.
Event: Any subset of sample space. Example: rolling even={2,4,6}.
Always count carefully: Sample space must be exhaustive and outcomes equally likely.
Calculating probabilities
Worked example
Die rolled. Find P(even), P(>3).
Solution
- S={1,2,3,4,5,6}
- P(even)=3/6=1/2
- P(>3)=3/6=1/2
Final answer
Both are 1/2.
Learn what examiners really want
See exactly what to write to score full marks. Our AI shows you model answers and the key phrases examiners look for.
Theoretical vs empirical probability
| Type | Definition |
|---|---|
| Theoretical | Based on logic (equally likely) |
| Empirical | Relative frequency from trials |
Worked example
Coin: theory P(H)=0.5. 100 flips give 52 heads. Empirical P(H)?
Solution
- Empirical=52/100=0.52
- More trials: empirical approaches theoretical
Final answer
Empirical=0.52.
Complementary and mutually exclusive
Complementary: Events covering all: P(A)+P(Ac)=1. Example: heads or tails.
Mutually exclusive: Cannot happen together: P(A and B)=0. Example: rolling 2 AND 3.
Worked example
P(rain)=0.3. Find P(no rain).
Solution
- P(no rain)=1-0.3=0.7
- Mutually exclusive AND complementary
Final answer
0.7.