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Basic Probability โ€‹

Spec reference: Probability
Key idea: Calculate probabilities, use probability notation and understand experimental vs theoretical probability.


โ–ถ Sets and Venn Diagrams


Probability scale โ€‹

Probability is measured from 0 (impossible) to 1 (certain).

P(event)=number of favourable outcomestotal number of outcomes

Basic probability โ€‹

Example

A bag contains 3 red, 5 blue and 2 green balls. A ball is picked at random.

P(red)=310

P(blue)=510=12

P(green)=210=15


Complementary events โ€‹

P(event does NOT happen)=1โˆ’P(event happens)

Example

P(rain)=0.35

P(no rain)=1โˆ’0.35=0.65


Mutually exclusive events โ€‹

Events that cannot happen at the same time.

P(Aย orย B)=P(A)+P(B)

For all mutually exclusive outcomes: โˆ‘P=1


Expected frequency โ€‹

Expected frequency=P(event)ร—number of trials

Example

A biased coin has P(heads)=0.6. In 200 flips, how many heads are expected?

0.6ร—200=120


Relative frequency (experimental probability) โ€‹

Relative frequency=number of times event occurredtotal number of trials

The more trials, the closer relative frequency gets to the true theoretical probability.


Sample space diagrams โ€‹

List all possible outcomes to find probabilities.

Example

Two dice are rolled. Find P(sum=7).

The sample space has 6ร—6=36 outcomes. Pairs that sum to 7: (1,6), (2,5), (3,4), (4,3), (5,2), (6,1) = 6 outcomes.

P(sum=7)=636=16


Exam tips โ€‹

Watch out for

  • Probabilities must be between 0 and 1 inclusive
  • All probabilities for mutually exclusive exhaustive events must add to 1
  • Theoretical probability assumes equally likely outcomes; experimental probability is based on results

Test Yourself โ€‹

Question 1 of 5

Bag: 4 red, 6 blue, 2 green. P(red)?

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