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Conditional Probability and Intersection of Events Section 13.3
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Objective 1. Find the probability of one event and a second event occurring. 2. Compute conditional probabilities.
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Key Term: Conditional Probability – the probability of event B, assuming that event A has already occurred, We denote this probability by P(B/A). Independent Events – two events that their occurrence has no effect on the probability of the other. Dependent Events – two events that their occurrence has an effect on the probability of the other.
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Key Concept: Special Rule for Computing P(F/E) by Counting If E and F are events in a sample space with equally likely outcomes then P(F/E) = n(E ∩ F) = number of outcomes common to E and F n(E) number of outcomes in E
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Key Concept: General Rule for Computing P(F/E) If E and F are events in a sample space with equally likely outcomes then P(F/E) = P(E ∩ F) P(E)
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Example 1: Compute P(F/E) TB pg. 754/5
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Example 2: Compute P(F/E) TB pg. 754/7
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Example 3: Find the probability TB pg. 754/11
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Example 4: Compute P(E/F) and P(F/E) TB pg. 754/15
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Example 5: Find P(F/E) TB pg. 755/17
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Example 6: Find P(F/E) TB pg. 755/19
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Example 7: TB pg. 755/33
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Example 8: TB pg. 755/37
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Example 9: TB pg. 755/43
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Key Concept: And Probabilities with Independent Events If A and B are independent events, then P(A and B) = P(A) * P(B). And Probabilities with Dependent Events If A and B are dependent events, then P(A and B) = P(A) * P(B given that A has occurred).
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Example 10: TB pg. 755/47
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Example 11: TB pg. 756/51
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Example 12: TB pg. 756/55
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Section 13.3 Assignment Classwork: ▫ TB pg. 754/6 – 20 Even, and 34 – 56 Even ▫ Remember you must write problem and show ALL work to receive credit for this assignment. ▫ DUE Tuesday, 11/ 22/11
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