+ Chapter 5 Probability: What Are the Chances? 5.1Randomness, Probability, and Simulation 5.2Probability Rules 5.3Conditional Probability and Independence After this section, you should be able to… DEFINE conditional probability COMPUTE conditional probabilities DESCRIBE chance behavior with a tree diagram DEFINE independent events DETERMINE whether two events are independent APPLY the general multiplication rule to solve probability questions Learning Objectives

+ Conditional Probability and Independence What is Conditional Probability? The probability we assign to an event can change if we know that some other event has occurred. This idea is the key to many applications ofprobability. When we are trying to find the probability that one event will happen under the condition that some other event is already known to have occurred, we are trying to determine a conditional probability. Definition: The probability that one event happens given that another event is already known to have happened is called a conditional probability. Suppose we know that event A has happened. Then the probability that event B happens given that event A has happened is denoted by P(B | A). Read | as “given that” or “under the condition that”

+ Example: Grade Distributions Consider the two-way table on page 314. Define events E : the grade comes from an EPS course, and L : the grade is lower than a B. Conditional Probability and Independence Find P(L) Find P(E | L) Find P(L | E) Total Total

+ Tree Diagrams We learned how to describe the sample space S of a chance process in Section 5.2. Another way to model chancebehavior that involves a sequence of outcomes is to constructa tree diagram. Conditional Probability and Independence Consider flipping a coin twice. What is the probability of getting two heads? Sample Space: HH HT TH TT So, P(two heads) = P(HH) = 1/4

+ General Multiplication Rule The idea of multiplying along the branches in a tree diagram leads to a general method for finding the probability P ( A ∩ B ) that two events happen together. Conditional Probability and Independence The probability that events A and B both occur can be found using the general multiplication rule P(A ∩ B) = P(A) P(B | A) where P(B | A) is the conditional probability that event B occurs given that event A has already occurred. General Multiplication Rule

For any two events A and B, P(A and B) = P(A) ∙ P(B|A) P(A and B) = P(B) ∙ P(A|B) The probability of A and B occurring jointly is the probability that B occurs given that A has already occurred multiplied by the probability that A occurs ∙

+ Example: Teens with Online Profiles The Pew Internet and American Life Project finds that 93% of teenagers (ages 12 to 17) use the Internet, and that 55% of online teens have posted a profileon a social-networking site. What percent of teens are online and have posted a profile?

+ Example: Who Visits YouTube? See the example on page 320 regarding adult Internet users.What percent of all adult Internet users visit video-sharing sites? P(video yes ∩ 18 to 29) = P(video yes ∩ 30 to 49) = P(video yes ∩ 50 +) = P(video yes) =

+ Independence: A Special Multiplication Rule When events A and B are independent, we can simplify the general multiplication rule since P ( B | A ) = P ( B ). Conditional Probability and Independence Definition: Multiplication rule for independent events If A and B are independent events, then the probability that A and B both occur is P(A ∩ B) = P(A) P(B) Following the Space Shuttle Challenger disaster, it was determined that the failure of O-ring joints in the shuttle’s booster rockets was to blame. Under cold conditions, it was estimated that the probability that an individual O-ring joint would function properly was Assuming O-ring joints succeed or fail independently, what is the probability all six would function properly? Example:

Two events A and B are independent if knowing that one occurs does not change the probability that the other occurs. If A and B are independent, then P(A and B) = P(A) ∙ P(B) If asked if two events are independent, you would prove this by showing that this formula holds true. P(A and B) = P(A) ∙ P(B) You can also show independence by showing that P(A) = P(A|B) Are disjoint events independent?

+ Conditional Probability and Independence Are the events “male” and “left-handed” independent? Justify your answer. Example:

+ Calculating Conditional Probabilities If we rearrange the terms in the general multiplication rule, we can get a formula for the conditional probability P ( B | A ). Conditional Probability and Independence P(A ∩ B) = P(A) P(B | A) General Multiplication Rule To find the conditional probability P(B | A), use the formula Conditional Probability Formula P(A ∩ B)P(B | A)P(A)P(A) =

+ Example: Who Reads the Newspaper? In Section 5.2, we noted that residents of a large apartment complex can be classified based on the events A : reads USA Today and B : reads the New York Times. The Venn Diagram below describes the residents. What is the probability that a randomly selected resident who reads USA Today also reads the New York Times ? Conditional Probability and Independence

+ Section 5.3 Conditional Probability and Independence In this section, we learned that… If one event has happened, the chance that another event will happen is a conditional probability. P(B|A) represents the probability that event B occurs given that event A has occurred. Events A and B are independent if the chance that event B occurs is not affected by whether event A occurs. If two events are mutually exclusive (disjoint), they cannot be independent. When chance behavior involves a sequence of outcomes, a tree diagram can be used to describe the sample space. The general multiplication rule states that the probability of events A and B occurring together is P(A ∩ B)=P(A) P(B|A) In the special case of independent events, P(A ∩ B)=P(A) P(B) The conditional probability formula states P(B|A) = P(A ∩ B) / P(A) Summary

+ Homework: #63-70, 77, 83, 84, 87 We’ll learn how to describe chance processes using the concept of a random variable. We’ll learn about Discrete and Continuous Random Variables Transforming and Combining Random Variables Binomial and Geometric Random Variables In the next Chapter…

Using a deck of playing cards: Initiating a game and starting to deal out cards, what is the likelihood a person is dealt a Heart? Conditional Probability – Example #1 If the person is dealt a heart, what is NOW the likelihood the person is again dealt a heart (i.e., without replacement)?

Conditional Probability – Example #2 Suppose that for a certain Caribbean island in any 3-year period: the probability of a major hurricane is.25, the probability of water damage is.44, and the probability of both a hurricane and water damage is.22. What is the probability of water damage given that there is a hurricane?

If P(A) = 0.45, P(B) = 0.35, and A & B are independent, find P(A or B). Is A & B disjoint? Conditional Probability – Example #3

Suppose I will pick two cards from a standard deck without replacement. What is the probability that I select two spades? Are the cards independent? NO Conditional Probability – Example #4

In a recent study it was found that the probability that a randomly selected student is a girl is.51 and a girl that plays sports is.10. If the student is female, what is the probability that she plays sports? Conditional Probability – Example #5

Conditional Probability TABLES – Example #6 A survey was given to 200 college students. The data breakdown of gender and pierced ears is listed below, with defined events: Using the table, calculate the following probabilities: a) Probability of Male or Pierced Ears: b) Probability of Male and Pierced Ears: Pierced Ears? GenderYesNoTotal Male Female Total

Conditional Probability Tables – Example #6 cont. c) Find the probability the student is Male, given the student has pierced ears. Pierced Ears? GenderYesNoTotal Male Female Total d) Find the probability the student is Female, given that the student has pierced ears. e) Find the probability the student is Female, given that the student does not have pierced ears.

Conditional Probability TREE DIAGRAMS– Example #7 Leah is flying from Boston to Denver with a connection in Chicago. The probability her first flight leaves on time is.15. If the flight is on time, the probability that her luggage will make the connecting flight in Chicago is.95, but if the first flight is delayed, the probability the luggage will make it is only.65. a)Are the first flight leaving in time and the luggage making the connection independent events? b)What is the probability that her luggage arrives in Denver with her? c)Suppose you pick up Leah in Denver and her luggage is not there. What is the probability that Leah’s first flight is delayed?

a)Are the first flight leaving in time and the luggage making the connection independent events? b)What is the probability that her luggage arrives in Denver with her? c)Suppose you pick up Leah in Denver and her luggage is not there. What is the probability that Leah’s first flight is delayed? Delayed On Time