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+ Chapter 5 Probability: What Are the Chances? 5.1 5.2 5.3 Randomness, Probability, and Simulation Probability Rules Conditional Probability and Independence Section 5.2 Probability Rules Learning Objectives After this section, you should be able to… DESCRIBE chance behavior with a probability model DEFINE and APPLY basic rules of probability DETERMINE probabilities from two-way tables CONSTRUCT Venn diagrams and DETERMINE probabilities Sample Space - the collection of all possible outcomes of a chance experiment Roll a die S = {1,2,3,4,5,6} Event - any collection of outcomes from the sample space - Complement Consists of all outcomes that are not in the event - Not rolling a even # = 1- P(rolling an even #) Union - the event A or B happening consists of all outcomes that are in at least one of the two events E A U B - Rolling a prime # or even number E={2,3,4,5,6} Intersection - the event A and B happening consists of all outcomes that are in both events E AB - Drawing a red card and a “2” E = {2 hearts, 2 diamonds} Mutually Exclusive (disjoint) -two events that have no outcomes in common - Roll a “2” or a “5” Addition rule: If A and B are disjoint events, then P(A or B ) = P(A) + P(B) If A and B are NOT disjoint events, then P(A or B ) = P(A) + P(B) – P (A ∩ B ) Multiplication rule: If there are n ways to do a first event & m ways to do a second event. Then the number of all possible outcomes = n∙m At least one: The probability that at least one outcome happens is 1 minus the probability that no outcomes happen. P(at least 1) = 1 – P(none) Disjoint example: A large auto center sells cars made by many different manufacturers. Three of these are Honda, Nissan, and Toyota. Suppose that P(H) = .25, P(N) = .18, P(T) = .14. Are these disjoint events? P(H or N or T) = yes .25 + .18+ .14 = .57 P(not (H or N or T) = 1 - .57 = .43 NonDisjoint example: Musical styles other than rock and pop are becoming more popular. A survey of college students finds that the probability they like country music is .40. The probability that they liked jazz is .30 and that they liked both is .10. Are these disjoint events? No What is the probability that they like country or jazz? P(C or J) = .4 + .3 -.1 = .6 For a sales promotion the manufacturer places winning symbols under the caps of 10% of all Dr. Pepper bottles. You buy a six-pack. What is the probability that you win something? P(at least one winning symbol) = 1 – P(no winning symbols) 1- 6 .9 1 - .531441= .4686 Rules of probability SUMMARY • What is the range of values for any given probability? 0 • What is the sum of the probability of all events? ≤ P(A) ≤ 1 Sum = 1 • Compliment rule: For any event A, P(Ac) = 1 – P(A) • Addition rule: If A and B are disjoint events, then P(A or B ) = P(A) + P(B) If A and B are NOT disjoint events, then P(A or B ) = P(A) + P(B) – P (A ∩ B ) Multiplication rule: If there are n ways to do a first event & m ways to do a second event. Then the number of all possible outcomes = n∙m • At least one: P(at least 1) = 1 – P(none) Simple Probability – Example # 1 • License plates in the State of Altered require 2 letters followed by 4 digits. No two letters can be the same, but it is ok to repeat digits. How many different license plates can me made? 26 ∙ 25 ∙ 10 ∙ 10 ∙ 10 ∙ 10 = 6,500,000 Probability example #2 : Roll the Dice + Simple You are rolling two fair, six-sided dice – one that’s red and one that’s green. Sample Space 36 Outcomes Since the dice are fair, each outcome is equally likely. Each outcome has probability 1/36. Probability Rules How many possible outcomes are there? There are 4 outcomes that result in a sum of 5. Since each outcome has probability 1/36, P(A) = 4/36. Suppose event B is defined as the “sum is not 5”. Find P(B). P(B) = 1 – 4/36 = 32/36 + Suppose event A is defined as the “sum of 5”. Find P(A). Probability Example #3: Distance Learning + Simple Distance-learning courses are rapidly gaining popularity among college students. Randomly select an undergraduate student who is taking distance-learning courses for credit and record the student’s age. Here is the probability model: Age group (yr): Probability: 18 to 23 24 to 29 30 to 39 40 or over 0.57 0.17 0.14 0.12 (a) Show that this is a legitimate probability model. Each probability is between 0 and 1 and 0.57 + 0.17 + 0.14 + 0.12 = 1 (b) Find the probability that the chosen student is not in the traditional college age group (18 to 23 years). P(not 18 to 23 years) = 1 – P(18 to 23 years) = 1 – 0.57 = 0.43 Simple Probability Example #4 Canada has 2 official languages, English and French. Choosing a Canadian at random in a recent survey gave the following distribution of responses: English French Asian/Pacific Other 0.63 0.22 0.06 ? What is the probability of ‘Other’? Why? 0.09, because the entire P(sample space) = 1 What is the probability that a Canadian’s “mother tongue” is not English? 1 – P (English) = 1 - 0.63 = .37 What is the probability that a Canadian’s mother tongue is either French or Asian Pacific? P(Fr) + P(AP) = 0.22+0.06 = .28 #5: Two-Way Tables Consider the example on page 303. Suppose we choose a student at random. Find the probability that the student (a) has pierced ears. (b) is a male with pierced ears. (c) is a male or has pierced ears. Define events A: is male and B: has pierced ears. (a) (b) Each (c) We want student to find is equally P(male likely or and pierced pierced to beears), chosen. ears), that that 103 is,is, students P(A P(A orand B).have There B). pierced Look90atmales are ears. the intersection in So, theP(pierced classofand the ears) 103 “Male” = individuals P(B) row =and 103/178. with “Yes”pierced column. ears. There are 19 males However, 19 males with pierced have pierced ears. So, ears P(A – don’t and B) count = 19/178. them twice! P(A or B) = (19 + 71 + 84)/178. So, P(A or B) = 174/178 Probability Rules When finding probabilities involving two events, a two-way table can display the sample space in a way that makes probability calculations easier. + Example Tree Diagrams - When there are many options, you may want to use a TREE DIAGRAM to help you find all the different combinations of outcomes. Simple Probability Example #6 – Four different people are each flipping a coin (4 distinct coin flips). What is the probability of getting... a) At least 2 heads? b) Either 3 heads or 3 tails? Example #6 – Four different people are each flipping a coin (4 distinct coin flips). What is the probability of getting... H H T H T H T H H T T H T T H T H T H T H T HHHH HHHT HHTH HHTT HTHH HTHT HTTH HTTT H T H T H T H T THHH THHT THTH THTT TTHH TTHT TTTH TTTT a) At least 2 heads? b) Either exactly 3 heads or 3 tails? Simple Probability Example #7 – In a family of 3 children… a) What is the probability exactly two are boys? b) What is the probability at least one is a girl? G G B B G B G GGG B G B G B G GGB B GBG GBB BGG BGB BBG BBB Venn Diagrams • NOT Disjoint: P(A ∩ B) • Disjoint: P(A ∪ B) There are 174 total people. You have 90 total males. 19 of them have their ears pierced. You have 103 total people with their ears pierced. Define event A as males Define event B as pierced ears. + Venn Diagrams Venn Diagrams Example #1 In an apartment complex, 40% of residents read the USA Today, while 25% of residents read the New York Times. Five percent of residents read both. Suppose we select an apartment resident at random and record which of the two papers the person reads. Find the probability the person reads at least 1 of the 2 papers. Find the probability the person doesn’t read either paper. Read USA Today 35% Read NY Times 5% 20% Topic D: Venn Diagrams Example #1 Find the probability the person reads at least 1 of the 2 papers. P(A or B) = P(A) + P(B) - P(A ∩ B) = .40 + .25 – .05 = .60 P(only A or only B or both) = .35 + .05 + .20 = .60 Find the probability the person doesn’t read either paper. 1 – P( at least one) = P (none) 1 - .60 = .40 .40 Read USA Today 35% Read NY Times 5% 20% Venn Diagrams Example #2 After observing several pizza orders, I discover the following pizza topping requests: 67 people wanted sausage on their pizza, 55 wanted pepperoni, 50 wanted mushrooms, 22 wanted sausage and mushrooms, 18 wanted pepperoni and mushrooms, 15 wanted sausage and pepperoni, and 10 wanted all three. What is the probability that a randomly selected person wants a) b) c) d) only sausage? pepperoni and mushrooms, but no sausage? pepperoni or sausage? Neither pepperoni nor sausage nor mushrooms? Pepperoni Sausage 40 32 5 pepperoni and mushrooms, but no sausage? 10 12 only sausage? 8 20 23 pepperoni or sausage? Mushrooms d) Neither pepperoni nor sausage nor mushrooms? + Section 5.2 Probability Rules Summary In this section, we learned that… A probability model describes chance behavior by listing the possible outcomes in the sample space S and giving the probability that each outcome occurs. An event is a subset of the possible outcomes in a chance process. For any event A, 0 ≤ P(A) ≤ 1 P(S) = 1, where S = the sample space If all outcomes in S are equally likely, P(AC) = 1 – P(A), where AC is the complement of event A; that is, the event that A does not happen. P(A) number of outcomes corresponding to event total number of outcomes in sample space A + Section 5.2 Probability Rules Summary In this section, we learned that… Events A and B are mutually exclusive (disjoint) if they have no outcomes in common. If A and B are disjoint, P(A or B) = P(A) + P(B). A two-way table or a Venn diagram can be used to display the sample space for a chance process. The intersection (A ∩ B) of events A and B consists of outcomes in both A and B. The union (A ∪ B) of events A and B consists of all outcomes in event A, event B, or both. The general addition rule can be used to find P(A or B): P(A or B) = P(A) + P(B) – P(A and B) + Homework: # 39, 40, 45, 46, 49, 50, 51–54, 56 In the next Section… We’ll learn how to calculate conditional probabilities as well as probabilities of independent events. We’ll learn about Conditional Probability Independence Tree diagrams and the general multiplication rule Special multiplication rule for independent events Calculating conditional probabilities notes on Venn Diagrams (Useful Note, the previous example illustrates the fact that we can’t use the addition rule for mutually exclusive events unless the events have no outcomes in common. The Venn diagram below illustrates why. Probability Rules Resource) + Additional Notes on Venn Diagrams (useful Because Venn diagrams have uses in other branches of mathematics, some standard vocabulary and notation have been developed. The complement AC contains exactly the outcomes that are not in A. The events A and B are mutually exclusive (disjoint) because they do not overlap. That is, they have no outcomes in common. Probability Rules resource) + Additional notes on Venn Diagrams (useful The intersection of events A and B (A ∩ B) is the set of all outcomes in both events A and B. Probability Rules resource) + Additional The union of events A and B (A ∪ B) is the set of all outcomes in either event A or B. Hint: To keep the symbols straight, remember ∪ for union and ∩ for intersection. Notes on Venn Diagrams (useful resource) Define events A: is male and B: has pierced ears. Probability Rules Recall the example on gender and pierced ears. We can use a Venn diagram to display the information and determine probabilities. + Additional