# AP Statistics - Chapter 6

## Terms

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- conditional probability
- when knowing one probability greatly effects the chances of the occurrence of another event
- Bayes' Rule
- P(A | B) = [ P(A|B1) * P(B1) ] / [ P(A|B1) * P(B1) + P(A|B2) * P(B2) ]
- P(A | B)
- P(A /\ B) / P(B)
- simple event
- any event consisting of exactly one outcome
- sample space
- the collection of all possible outcomes from a chance experiment
- A and B, A /\ B
- the event consisting of outcomes common to both events
- P(A U B)
- P(A) + P(B) - P(A /\ B)
- disjoint or mutually exclusive
- two events that have no common outcomes
- chance experiment
- any experiment for which there is uncertainty concerning the resulting outcome
- A or B, A U B
- the event consisting of all outcomes in at least one of the two events
- Law of Large Numbers
- as the number of repetitions of a chance experiment increases, the chance that the relative frequency of occurrence for an event will differ from the true probability of the event by more than any small number approaches 0
- not A, A^c
- the event consisting of all outcomes not in A
- P(A /\ B)
- P(A) * P(B), A and B are independent
- event
- any collection of outcomes from the sample space of a chance experiment
- independent events
- P(A | B) = P(A), knowledge that some number of the events have occurred does not change the probabilities that any particular one or more of the other events has occurred