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6.3 Conditional Probability
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Calculate Conditional Probabilities Determine if events are independent
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#1) 0 ≤ P(A) ≤ 1 #2) P(S) = 1 #3) #4) P(A or B)= P(A) + P(B) #5) P(A and B)= P(A) P(B)
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Joint event- (A and B) Joint probability- P(A and B)
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P(one or more of A, B, C)= P(A) + P(B) + P(C)
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For any two events A and B, P(A or B)= P(A) + P(B) – P(A and B)
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P(D)=0.7 P(M)=0.5 P(D and M)=0.3 Find a) P(D and Mʿ)= 0.4 b) P(Dʿ and Mʿ)= 0.1
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6.37: P(A or B)= P(A) + P(B) – P(A and B) = 0.125 + 0.237 – 0.077=0.285 6.38: P(A or B)= 0.8
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Ex: Pg. 347 P(married)= 58,929/99,585 P(married | age 18 to 24)= 3,046/12,614 P( married and 18 to 24) = 3,046/99,585
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When P(A)>0, the conditional probability of B given A is: P(B | A)= P (A and B) P(A)
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Ex: The probability that Mike has a Visa card is 0.45. The probability that Mike has a Visa and a Master card is 0.23. What is the probability that Mike has a Master card given he has a Visa? P(M | V)= P (M and V) = 0.23 = 0.51 P(V) 0.45
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Ex: Only 5% of male high school basketball, baseball, and football players go on to play at the college level. Of these, only 1.7% enter major league professional sports. About 40% of the athletes who compete in college and then reach the pros have a career of more than 3 years. Define these events: C= college after high school M= major league after college 3= 3 or more years of pro
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What is the probability that a high school athlete competes in college and then goes on to have a pro career of more than 3 years?
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Ex: The probability that a doctor is on call is 0.15. The probability that a doctor performs a surgery is 0.24. The probability a doctor performs a surgery and he is on call is 0.051. What is the probability the doctor is performing a surgery given he is on call? P(S | C)= P (S and C) = 0.051 = 0.34 P(C) 0.15
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Does P(S and C)= P(S) P(C) ?? 0. 051 ≠ 0.15 * 0.24 0.051 ≠ 0.036 therefore they are NOT independent
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