Math 227 Elementary Statistics Sullivan, 4th ed.

Copyright of the definitions and examples is reserved to Pearson Education, Inc.. In order to use this PowerPoint presentation, the required textbook for the class is the Fundamentals of Statistics, Informed Decisions Using Data, Michael Sullivan, III, fourth edition.

CHAPTER 5 Probability

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Probability is a measure of the likelihood of a random phenomenon or chance behavior. Probability describes the long-term proportion with which a certain outcome will occur in situations with short-term uncertainty. If we flip a coin 100 times and compute the proportion of heads observed after each toss of the coin, what will the proportion approach?

The Law of Large Numbers As the number of repetitions of a probability experiment increases, the proportion with which a certain outcome is observed gets closer to the probability of the outcome.

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Experiment – any activity that leads to well-defined results called outcomes. Outcome – the result of a single trial of probability experiment. Sample Space, – the set of all possible outcomes of a probability experiment. Event, – a subset of sample space. Simple event, – an event with one outcome is called a simple event. Compound event – consists of two or more outcomes.

Example 1 : A die is tossed one time Example 1 : A die is tossed one time. (a) List the elements of the sample space . (b) List the elements of the event consisting of a number that is greater than 4. (a) (b) Example 2 : A coin is tossed twice. List the elements of the sample space , and list the elements of the event consisting of at least one head.

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Objective B : Requirements for Probabilities 1. Each probability must lie on between 0 and 1. 2. The sum of probabilities for all simple events in equals 1. If an event is impossible, the probability of the event is 0. If an event is a certainty, the probability of the event is 1. An unusual event is an event that has a low probability of occurring. Typically, an event with a probability less than 0.05 is considered as unusual. Probabilities should be expressed as reduced fractions or rounded to three decimal places.

Example 1 : A probability experiment is conducted Example 1 : A probability experiment is conducted. Which of these can be considered a probability of an outcome? (a) (b) (c) Yes No No

Example 2 : Why is the following not a probability model? Color Probability Red 0.28 Green 0.56 Yellow 0.37 Condition 1 : Condition 2 : Check : Condition 2 was not met.

Example 3 : Given : and Find : Condition 1 : Condition 2 :

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Objective C : Calculating Probabilities C1. Approximating Probabilities Using the Empirical Approach (Relative Frequency Approximation of Probability) The probability of event is approximately the number of times event is observed divided by the number of repetitions of the experiment. Example 1 : Suppose that you roll a die 100 times and get six 80 times. Based on these results, what is the probability that the next roll results in six?

Example 2 : During a sale at men’s store, 16 white sweaters, 3 red sweaters, 9 blue sweaters and 7 yellow sweaters were purchased. If a customer is selected at random, find the probability that he bought a sweater that was not white.

(a) Between 30 and 39 years of age Example 3 : The age distribution of employees for this college is shown below: Age # of Employees Under 20 25 20 – 29 48 30 – 39 32 40 – 49 15 50 and over 10 If an employee is selected at random, find the probability that he or she is in the following age groups. (a) Between 30 and 39 years of age (b) Under 20 or over 49 years of age

C2. Classical Approach to Probability (Equally Likely Outcomes are required) If an experiment has equally likely outcomes and if the number of ways that an event can occur in , then the probability of , , is If is the sample space of this experiment, where is the number of outcomes in event , and is the number of outcomes in the sample space.

Example 1 : Let the sample space be Example 1 : Let the sample space be . Suppose the outcomes are equally likely. (a) Compute the probability of the event . (b) Compute the probability of the event “an odd number.”

Example 2 : Two dice are tossed Example 2 : Two dice are tossed. Find the probability that the sum of two dice is greater than 8.

Example 3 : If one card is drawn from a deck, find the probability of getting (a) a club; (b) a 4 and a club. (a) a club

(b) a 4 and a club

Example 4 : Three equally qualified runners, Mark, Bill, and Alan, run a 100-meter sprint, and the order of finish is recorded. (a) Give a sample space . (b) What is the probability that Mark will finish last? (a) (b)

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Event A and B are disjoint (mutually exclusive) if they have no outcomes in common. Addition Rule for Disjoint Events If E and F are disjoint events, then .

Example 1: A standard deck of cards contain 52 cards Example 1: A standard deck of cards contain 52 cards. One card is randomly selected from the deck. Compute the probability of randomly selecting a two or three from a deck of cards.

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Objective B : General Addition Rule The General Addition Rule for events that are Not Disjoint For any two events E and F,

Example 1 : A standard deck of cards contain 52 cards Example 1 : A standard deck of cards contain 52 cards. One card is randomly selected from the deck. Compute the probability of randomly selecting a two or club from a deck of cards.

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Objective C : Complement Rule If E represents any event and Ec represents the complement of E, then e.g. The chance of raining tomorrow is 70%. What is the probability that it will not rain tomorrow?

Example 1 : A probability experiment is conducted in which the sample space of the experiment is . Let event , event , and event . (a) List the outcome in E and F. Are E and F mutually exclusive? Since there are common elements of 5, 6, and 7 between E and F, E and F are not mutually exclusive. (b) Are F and G mutually exclusive? Explain. Yes, there is no common element between F and G.

(c) List the outcome in E or F (c) List the outcome in E or F. Find by counting the number of outcomes in E or F. (d) Determine using the General Addition Rule.

(e) List the outcome in EC (e) List the outcome in EC. Find by counting the number of outcomes in EC. (f) Determine using Complement Rule.

Example 2: In a large department store, there are 2 managers, 4 department heads, 16 clerks, and 4 stock persons. If a person is selected at random, (a) find the probability that the person is a clerk or a manager; (b) find the probability that the person is not a clerk. (a) (b)

(a) Verify that this is a probability model. Example 3: The following probability show the distribution for the number of rooms in U.S. housing units. Rooms Probability One 0.005 Two 0.011 Three 0.088 Four 0.183 Five 0.230 Six 0.204 Seven 0.123 Eight or more 0.156 Source: U.S. Censor Bureau (a) Verify that this is a probability model. Is each probability outcome between 0 and 1? Yes Is ? Yes

(b) What is the probability that a randomly selected housing unit has four or more rooms? Interpret this probability. Approximate 89.6% of housing unit has four or more rooms.

Example 4: According the U. S Example 4: According the U.S. Censor Bureau, the probability that a randomly selected household speaks only English at home is 0.81. The probability that a randomly selected household speaks only Spanish at home is 0.12. (a) What is the probability that a randomly selected household speaks only English or only Spanish at home? (b) What is the probability that a randomly selected household speaks a language other than only English at home? (c) Can the probability that a randomly selected household speaks only Polish at home equal to 0.08? Why or why not? No, because i.e.

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Objective D : Contingency Table A Contingency table relates two categories of data. It is also called a two-way table which consists of a row variable and a column variable. Each box inside a table is called a cell. Example 1 : In a certain geographic region, newspapers are classified as being published daily morning, daily evening and weekly. Some have a comics section and other do not. The distribution is shown here. (CY) (M) (E) (W) (CN) 6 9 5 7 3 15 Have Comics Section Morning Evening Weekly Yes 2 3 1 No 3 4 2

If a newspaper is selected at random, find these probabilities. (a) The newspaper is a weekly publication. (b) The newspaper is a daily morning publication or has comics . (c) The newspaper is a weekly or does not have comics .

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Two events are independent if the occurrence of event E does not affect the probability of event F. Two events are dependent if the occurrence of event E affects the probability of event F. Example 1 : Determine whether the events E and F are independent or dependent. Justify your answer. (a) E: The battery in your cell phone is dead. F: The battery in your calculator is dead. Independent (b) E: You are late to class. F: Your car runs out of gas. Dependent

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Objective B : Multiplication Rule for Independent Events If E and F are independent events, then . Example 1 : If 36% of college students are underweight, find the probability that if three college students are selected at random, all will be underweight. Independent case

Example 2 : If 25% of U. S. federal prison inmates are not U. S Example 2 : If 25% of U.S. federal prison inmates are not U.S. citizens, find the probability that two randomly selected federal prison inmates will be U.S. citizens. Independent case

Section 5.1 Probability Rule Objective A : Sample Spaces and Events Objective B : Requirements for Probabilities Objective C : Calculating Probabilities Section 5.2 The Additional Rules and Complements Objective A: Addition Rule for Disjoint (Mutually Exclusive) Events Objective B : General Addition Rule Objective C : Complement Rule Objective D : Contingency Table Section 5.3 Independence and Multiplication Rule Objective A : Independent Events Objective B : Multiplication Rule for Independent Events Objective C : At-Least Probabilities

Objective C : At-Least Probabilities Probabilities involving the phrase “at least” typically use the Complement Rule. The phrase at least means “greater than or equal to.” For example, a person must be at least 17 years old to see an R-rated movie.

Example 1 : If you make random guesses for four multiple-choice test questions (each with five possible answers), what is the probability of getting at least one correct? Direct method : Indirect method : What is the opposite of at least one correct? None is correct.

Example 2 : For the fiscal year of 2007, the IRS audited 1 Example 2 : For the fiscal year of 2007, the IRS audited 1.77% of individual tax returns with income of $100,000 or more. Suppose this percentage stays the same for the current fiscal year. (a) Would it be unusual for a return with income of $100,000 or more to be audited? Yes, 1.77% is unusually low chance of being audited. (In general, probability of less than 5% is considered to be unusual.) (b) What is the probability that two randomly selected returns with income of $100,000 or more to be audited? Let A be the return with income of $100,000 or more being audited.

(c) What is the probability that two randomly selected returns with income of $100,000 or more will NOT be audited? (d) What is the probability that at least one of the two randomly selected returns with income of $100,000 or more to be audited?

Section 5.5 Counting Techniques Section 5.4 Conditional Probability and the General Multiplication Rule Objective A : Conditional Probability and the General Multiplication Rule Objective B : Application Section 5.5 Counting Techniques Objective A : Multiplication Rule of Counting Objective B : Permutation or Combination Objective C : Using the Counting Techniques to Find Probabilities

Section 5.4 Conditional Probability and the General Multiplication Rule Objective A : Conditional Probability and the General Multiplication Rule A1. Multiplication Rule for Dependent Events If E and F are dependent events, then . The probability of E and F is the probability of event E occurring times the probability of event F occurring, given the occurrence of event E.

Example 1: A box has 5 red balls and 2 white balls Example 1: A box has 5 red balls and 2 white balls. If two balls are randomly selected (one after the other), what is the probability that they both are red? (a) With replacement → Independent case (b) Without replacement → Dependent case

Example 2: Three cards are drawn from a deck without replacement Example 2: Three cards are drawn from a deck without replacement. Find the probability that all are jacks. Without replacement → Dependent case (Almost zero percent of a chance)

A2. Conditional Probability If E and F are any two events, then . The probability of event F occurring, given the occurrence of event E, is found by dividing the probability of E and F by the probability of E.

Example 1 : At a local Country Club, 65% of the members play bridge and swim, and 72% play bridge. If a member is selected at random, find the probability that the member swims, given that the member plays bridge. Let B be the event of playing bridge. Let S be the event of swimming. Given : Find :

Section 5.5 Counting Techniques Section 5.4 Conditional Probability and the General Multiplication Rule Objective A : Conditional Probability and the General Multiplication Rule Objective B : Application Section 5.5 Counting Techniques Objective A : Multiplication Rule of Counting Objective B : Permutation or Combination Objective C : Using the Counting Techniques to Find Probabilities

Example 1 : Eighty students in a school cafeteria were asked if they favored a ban on smoking in the cafeteria. The results of the survey are shown in the table. (F) (Fa) (O) (N) (S) 50 30 38 32 10 80 Class Favor Oppose No opinion Freshman 15 27 8 Sophomore 23 5 2 If a student is selected at random, find these probabilities. (a) The student is a freshman or favors the ban.

(b) Given that the student favors the ban, the student is a sophomore.

Example 2 : The local golf store sells an “onion bag” that contains 35 “experienced” golf balls. Suppose that the bag contains 20 Titleists, 8 Maxflis and 7 Top-Flites. (a) What is the probability that two randomly selected golf balls are both Titleists? Without replacement → Dependent case (b) What is the probability that the first ball selected is a Titleist and the second is a Maxfli? Without replacement → Dependent case

(c) What is the probability that the first ball selected is a Maxfli and the second is a Titleist? Without replacement → Dependent case (d) What is the probability that one golf ball is a Titleist and the other is a Maxfli? Without replacement → Dependent case

Section 5.5 Counting Techniques Objective B : Permutation and Combination Permutation The number of ways we can arrange distinct objects, taking them at one time, is Order matters Combination The number of distinct combinations of distinct objects that can be formed, taking them at one time, is Order doesn’t matters

Example 1: Given the letters A, B, C, and D, list the permutations and combinations for selecting two letters. The permutations are AB BA CA DA AC BC CB DB AD BD CD DC Note: AB = BA in combination. Therefore, if duplicates are removed from a list of permuations, what is left is a list of combinations. The combinations are AB BA CA DA AC BC CB DB AD BD CD DC

Example 1 : Find (a) (b) (c) (d)

Example 2 : An inspector must select 3 tests to perform in a certain order on a manufactured part. He has a choice of 7 tests. How many ways can be performed 3 different tests? Example 3 : If a person can select 3 presents from 10 presents, how many different combinations are there?

Section 5.5 Counting Techniques Section 5.4 Conditional Probability and the General Multiplication Rule Objective A : Conditional Probability and the General Multiplication Rule Objective B : Application Section 5.5 Counting Techniques Objective A : Multiplication Rule of Counting Objective B : Permutation or Combination Objective C : Using the Counting Techniques to Find Probabilities

Section 5.5 Counting Techniques Objective C : Using the Counting Techniques to Find Probabilities , we can calculate by the formula . After using the multiplication rule, combination and permutation learned from this section to count the number of outcomes for a sample space, and the number of outcomes for an event,

Example 1 : A Social Security number is used to identify each resident of the United States uniquely. The number is of the form xxx-xx-xxxx, where each x is a digit from 0 to 9. (a) How many Social Security numbers can be formed? (b) What is the probability of correctly guessing the Social Security number of the President of the United States?

Example 2 : Suppose that there are 55 Democrats and 45 Republicans in the U.S. Senate. A committee of seven senators is to be formed by selecting members of the Senate randomly. (a) What is the probability that the committee is composed of all Democrats? (b) What is the probability that the committee is composed of all Republicans?

(c) What is the probability that the committee is composed of all three Democrats and four Republicans?

Example 3 : Five cards are selected from a 52-card deck for a poker hand. (A poker hand consists of 5 cards dealt in any order.) (a) How many outcomes are in the sample space? (b) A royal flush is a hand that contains that A, K, Q, J, 10, all in the same suit. How many ways are there to get a royal flush? A, K, Q, J, 10 - ♠ A, K, Q, J, 10 -♥ n(A) = 4 combinations A, K, Q, J, 10 - ♣ A, K, Q, J, 10 - ♦ (c) What is the probability of being dealt a royal flush?

5.6 Putting It Together: Which Method Do I Use?

Objectives Determine the appropriate probability rule to use Determine the appropriate counting technique to use 74

Objective 1 Determine the Appropriate Probability Rule to Use 75

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