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3 Probability Psychology Weather forecast Business Elementary Statistics Larson Farber Games Medicine Sports Larson/Farber Ch. 3 Section 3.1 Basic Concepts of Probability Larson/Farber Ch. 3 Important Terms Probability experiment: Roll a die An action through which counts, measurements or responses are obtained Sample space: {1 2 3 4 5 6} The set of all possible outcomes Event: { Die is even } = { 2 4 6 } A subset of the sample space. Outcome: {4} The result of a single trial Larson/Farber Ch. 3 Another Experiment Probability Experiment: An action through which counts, measurements, or responses are obtained Choose a car from production line Sample Space: The set of all possible outcomes Event: A subset of the sample space. Outcome: The result of a single trial Larson/Farber Ch. 3 Types of Probability Classical (equally probable outcomes) Empirical Probability blood pressure will decrease after medication Intuition Probability the line will be busy Larson/Farber Ch. 3 Tree Diagrams Two dice are rolled. Describe the sample space. 1st roll 1 2 1 2 3 4 5 6 Start 3 4 5 6 1 2 3 4 5 6 12 3 4 5 61 2 3 4 5 6 1 2 3 4 5 6 1 2 3 4 5 6 2nd roll 36 outcomes Larson/Farber Ch. 3 Sample Space and Probabilities Two dice are rolled and the sum is noted. 1,1 1,2 1,3 1,4 1,5 1,6 2,1 2,2 2,3 2,4 2,5 2,6 3,1 3,2 3,3 3,4 3,5 3,6 4,1 4,2 4,3 4,4 4,5 4,6 5,1 5,2 5,3 5,4 5,5 5,6 6,1 6,2 6,3 6,4 6,5 6,6 Find the probability the sum is 4. 3/36 = 1/12 = 0.083 Find the probability the sum is 11. 2/36 = 1/18 = 0.056 Find the probability the sum is 4 or 11. Larson/Farber Ch. 3 5/36 = 0.139 Complementary Events The complement of event E is event E´. E´ consists of all the events in the sample space that are not in event E. E E´ P(E´) = 1 - P(E) The day’s production consists of 12 cars, 5 of which are defective. If one car is selected at random, find the probability it is not defective. Solution: P(defective) = 5/12 P(not defective) = 1 - 5/12 = 7/12 = 0.583 Larson/Farber Ch. 3 Section 3.2 Conditional Probability and the Multiplication Rule Larson/Farber Ch. 3 Conditional Probability The probability an event B will occur, given (on the condition) that another event A has occurred. We write this as P(B|A) and say “probability of B, given A.” Two cars are selected from a production line of 12 cars where 5 are defective. What is the probability the 2nd car is defective, given the first car was defective? Given a defective car has been selected, the conditional sample space has 4 defective out of 11. P(B|A) = 4/11 Larson/Farber Ch. 3 Independent Events Two dice are rolled. Find the probability the second die is a 4 given the first was a 4. Original sample space: {1, 2, 3, 4, 5, 6} Given the first die was a 4, the conditional sample space is: {1, 2, 3, 4, 5, 6} The conditional probability, P(B|A) = 1/6 Larson/Farber Ch. 3 Independent Events Two events A and B are independent if the probability of the occurrence of event B is not affected by the occurrence (or non-occurrence) of event A. A = Being female B = Having type O blood A = 1st child is a boy B = 2nd child is a boy Two events that are not independent are dependent. A = taking an aspirin each day B = having a heart attack Larson/Farber Ch. 3 A = being a female B = being under 64” tall Independent Events If events A and B are independent, then P(B|A) = P(B) Conditional Probability Probability 12 cars are on a production line where 5 are defective and 2 cars are selected at random. A = first car is defective B = second car is defective. The probability of getting a defective car for the second car depends on whether the first was defective. The events are dependent. Two dice are rolled. A = first is a 4 and B = second is a 4 P(B) = 1/6 and P(B|A) = 1/6. The events are independent. Larson/Farber Ch. 3 Contingency Table The results of responses when a sample of adults in 3 cities was asked if they liked a new juice is: Omaha Yes 100 No 125 Undecided 75 Total 300 Seattle 150 130 170 450 Miami 150 95 5 250 Total 400 350 250 1000 One of the responses is selected at random. Find: 1. P(Yes) 2. P(Seattle) 3. P(Miami) 4. P(No, given Miami) Larson/Farber Ch. 3 Solutions Yes No Undecided Total Omaha 100 125 75 300 1. P(Yes) Seattle 150 130 170 450 Miami 150 95 5 250 = 400 / 1000 = 0.4 2. P(Seattle) = 450 / 1000 = 0.45 3. P(Miami) = 250 / 1000 = 0.25 4. P(No, given Miami) = 95 / 250 = 0.38 Answers: 1) 0.4 Larson/Farber Ch. 3 Total 400 350 250 1000 2) 0.45 3) 0.25 4) 0.38 Multiplication Rule To find the probability that two events, A and B will occur in sequence, multiply the probability A occurs by the conditional probability B occurs, given A has occurred. P(A and B) = P(A) x P(B|A) Two cars are selected from a production line of 12 where 5 are defective. Find the probability both cars are defective. A = first car is defective B = second car is defective. P(A) = 5/12 P(B|A) = 4/11 P(A and B) = 5/12 x 4/11 = 5/33 = 0.1515 Larson/Farber Ch. 3 Multiplication Rule Two dice are rolled. Find the probability both are 4’s. A = first die is a 4 and B = second die is a 4. P(A) = 1/6 P(B|A) = 1/6 P(A and B) = 1/6 x 1/6 = 1/36 = 0.028 When two events A and B are independent, then P (A and B) = P(A) x P(B) Note for independent events P(B) and P(B|A) are the same. Larson/Farber Ch. 3 Section 3.3 The Addition Rule Larson/Farber Ch. 3 Compare “A and B” to “A or B” The compound event “A and B” means that A and B both occur in the same trial. Use the multiplication rule to find P(A and B). The compound event “A or B” means either A can occur without B, B can occur without A or both A and B can occur. Use the addition rule to find P(A or B). B A A and B Larson/Farber Ch. 3 B A A or B Mutually Exclusive Events Two events, A and B, are mutually exclusive if they cannot occur in the same trial. A = A person is under 21 years old B = A person is running for the U.S. Senate A = A person was born in Philadelphia B = A person was born in Houston A B Mutually exclusive P(A and B) = 0 When event A occurs it excludes event B in the same trial. Larson/Farber Ch. 3 Non-Mutually Exclusive Events If two events can occur in the same trial, they are non-mutually exclusive. A = A person is under 25 years old B = A person is a lawyer A = A person was born in Philadelphia B = A person watches West Wing on TV A and B Non-mutually exclusive P(A and B) ≠ 0 Larson/Farber Ch. 3 A B The Addition Rule The probability that one or the other of two events will occur is: P(A) + P(B) – P(A and B) A card is drawn from a deck. Find the probability it is a king or it is red. A = the card is a king B = the card is red. P(A) = 4/52 and P(B) = 26/52 but P(A and B) = 2/52 P(A or B) = 4/52 + 26/52 – 2/52 = 28/52 = 0.538 Larson/Farber Ch. 3 The Addition Rule A card is drawn from a deck. Find the probability the card is a king or a 10. A = the card is a king B = the card is a 10. P(A) = 4/52 and P(B) = 4/52 and P(A and B) = 0/52 P(A or B) = 4/52 + 4/52 – 0/52 = 8/52 = 0.054 When events are mutually exclusive, P(A or B) = P(A) + P(B) Larson/Farber Ch. 3 Contingency Table The results of responses when a sample of adults in 3 cities was asked if they liked a new juice is: Omaha Yes 100 No 125 Undecided 75 Total 300 Seattle 150 130 170 450 Miami 150 95 5 250 Total 400 350 250 1000 One of the responses is selected at random. Find: 1. P(Miami and Yes) 3. P(Miami or Yes) 2. P(Miami and Seattle) 4. P(Miami or Seattle) Larson/Farber Ch. 3 Contingency Table Yes No Undecided Total Omaha 100 125 75 300 Seattle 150 130 170 450 Miami 150 95 5 250 Total 400 350 250 1000 One of the responses is selected at random. Find: 1. P(Miami and Yes) = 250/1000 • 150/250 = 150/1000 = 0.15 2. P(Miami and Seattle) = 0 Larson/Farber Ch. 3 Contingency Table Yes No Undecided Total Omaha 100 125 75 300 Seattle 150 130 170 450 Miami 150 95 5 250 Total 400 350 250 1000 3 P(Miami or Yes) 250/1000 + 400/1000 – 150/1000 = 500/1000 = 0.5 4. P(Miami or Seattle) 250/1000 + 450/1000 – 0/1000 = 700/1000 = 0.7 Larson/Farber Ch. 3 Summary For complementary events P(E') = 1 - P(E) Subtract the probability of the event from one. The probability both of two events occur P(A and B) = P(A) • P(B|A) Multiply the probability of the first event by the conditional probability the second event occurs, given the first occurred. Probability at least one of two events occur P(A or B) = P(A) + P(B) - P(A and B) Add the simple probabilities, but to prevent double counting, don’t forget to subtract the probability of both occurring. Larson/Farber Ch. 3 Section 3.4 Counting Principles Larson/Farber Ch. 3 Fundamental Counting Principle If one event can occur m ways and a second event can occur n ways, the number of ways the two events can occur in sequence is m • n. This rule can be extended for any number of events occurring in a sequence. If a meal consists of 2 choices of soup, 3 main dishes and 2 desserts, how many different meals can be selected? Dessert Soup Main Start 2 Larson/Farber Ch. 3 • 3 • 2 = 12 meals Factorials Suppose you want to arrange n objects in order. There are n choices for 1st place. Leaving n – 1 choices for second, then n – 2 choices for third place and so on until there is one choice of last place. Using the Fundamental Counting Principle, the number of ways of arranging n objects is: n(n – 1)(n – 2)…1 This is called n factorial and written as n! Larson/Farber Ch. 3 Permutations A permutation is an ordered arrangement. The number of permutations for n objects is n! n! = n (n – 1) (n – 2)…..3 • 2 • 1 The number of permutations of n objects taken r at a time (where r £ n) is: You are required to read 5 books from a list of 8. In how many different orders can you do so? There are 6720 permutations of 8 books reading 5. Larson/Farber Ch. 3 Combinations A combination is a selection of r objects from a group o f n objects. The number of combinations of n objects taken r at a time is You are required to read 5 books from a list of 8. In how many different ways can you choose the books if order does not matter. There are 56 combinations of 8 objects taking 5. Larson/Farber Ch. 3 1 2 3 4 Combinations of 4 objects choosing 2 1 2 3 1 1 4 2 3 3 4 2 4 Each of the 6 groups represents a combination. Larson/Farber Ch. 3 1 2 4 3 Permutations of 4 objects choosing 2 1 1 1 2 3 2 3 4 4 1 1 1 2 3 3 4 3 4 2 3 2 4 4 2 Each of the 12 groups represents a permutation. Larson/Farber Ch. 3