13.3 conditional probability and intersections of events understand how to compute conditional...
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13.3 Conditional Probability and Intersections of Events
• Understand how to compute conditional probability.
• Calculate the probability of the intersection of two events.
• Use probability trees to compute conditional probabilities.
• Understand the difference between dependent and independent events.
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Conditional probability takes into account that one event occurring may change the probability of a 2nd event.
• When we compute the probability of event F assuming that the event E has already occurred, this is called the conditional probability of F, given E.– We denote this as P(F | E). “The
probability of F given E.”– If E and F are events in a sample space
with equally likely outcomes, then P(F | E)=n(EF)
n(E)
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• Assume we roll two dice and the total showing is greater than nine. What is the probability that the total is odd?
– This sample space has 36 equally likely outcomes. Let G stand for the roll being greater than nine and O stand for the total being odd.
– The number of outcomes in G are 6: (4,6), (5,5), (5,6), (6,4), (6,5), (6,6). The number of outcomes of O G are 2: (5,6) and (6,5).
– P(O | G) = n(O G) = 2 = 1 n(G) 6 3
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• General Rule for Computing P(F|E): If E and F are events in a sample space, then P(F | E) = P(E F) P(E)– This rule is used when the sample
space is not equally likely or in a situation where it is not possible to count the outcomes. This rule is based on probability rather than counting.
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We use conditional probability to find the probability of the intersection of two events.
• Rule for Computing the Probability of the Intersection of Events – If E and F are two events, then P(E F) = P(E) • P(F | E)
• We draw two cards without replacement from a standard 52-card deck. What is the probability that both cards are kings?– P(A B) = P(A) • P(B | A)
4 • 3 = 0.0045 52 51
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Trees help you visualize probability computations.
• We can represent an experiment that happens in stages with a tree whose branches represent the outcomes of the experiment. We calculate the probability of an outcome by multiplying the probabilities found along the branch representing that outcome.
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Independent events have no effect on each other’s probabilities.
• Events E and F are independent events if P(F | E) = P(F).– If E and F are independent, then
knowing that E has occurred does not influence the way we compute the probability of F
• Events E and F are dependent events if P(F | E) ≠ P(F)
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Classwork/Homework
• Classwork – Page 757 (7 – 10, 23 – 35 odd, 41, 43, 67, 69)
• Homework – Page 757 (11 – 14, 24 – 36 even, 42, 44, 68, 70)
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Dice Table
1 2 3 4 5 6
1(1,1)
(1,2)
(1,3)
(1,4)
(1,5)
(1,6)
2(2,1)
(2,2)
(2,3)
(2,4)
(2,5)
(2,6)
3(3,1)
(3,2)
(3,3)
(3,4)
(3,5)
(3,6)
4(4,1)
(4,2)
(4,3)
(4,4)
(4,5)
(4,6)
5(5,1)
(5,2)
(5,3)
(5,4)
(5,5)
(5,6)
6(6,1)
(6,2)
(6,3)
(6,4)
(6,5)
(6,6)