1. Pull 2 samples of 3 pennies and record both averages (2 dots).
We are going to discuss 5.3 today.

2. Chapter 5 Probability: What Are the Chances? Section 5.3
Conditional Probability and Independence

3. Conditional Probability and Independence
CALCULATE and INTERPRET conditional probabilities.
DETERMINE if two events are independent.
USE the general multiplication rule to CALCULATE probabilities.
USE a tree diagram to model a chance process involving a sequence of outcomes and to CALCULATE probabilities.
When appropriate, USE the multiplication rule for independent events to CALCULATE probabilities.

4. 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 of probability.

5. 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 of probability.
The probability that one event happens given that another event is known to have happened is called a conditional probability. The conditional probability that event B happens given that event A has happened is denoted by P(B|A).

6. 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 of probability.
The probability that one event happens given that another event is known to have happened is called a conditional probability. The conditional 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”

7. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock

8. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock
(a) P(T|S) = P(third-class | survived)

9. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock
(a) P(T|S) = P(third-class | survived)
= 151 / 442

10. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock
(a) P(T|S) = P(third-class | survived)
= 151 / 442

11. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock
(a) P(T|S) = P(third-class | survived)
= 151 / 442
= 0.342

12. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock
(a) Given that the randomly chosen person survived, there is about a 34.2% chance that she or he was a third-class passenger.

13. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock
(b) P(survived| not first-class) = P(S|FC)

14. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock
(b) P(survived| not first-class) = P(S|FC) =

15. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock
(b) P(survived| not first-class) = P(S|FC) =

16. What Is Conditional Probability?
Problem: In 1912, the luxury liner Titanic, on its first voyage across the
Atlantic, struck an iceberg and sank. Some passengers got off the ship in lifeboats, but many died. Suppose we randomly select one of the adult passengers from the Titanic. Define events F: first-class passenger, S: survived, and T: third-class passenger.
Find P(T | S). Interpret this value in context.
Given that the chosen person is not a first-class passenger, what’s the probability that she or he survived? Write your answer as a probability statement using correct symbols for the events.
Images Group/REX/Shutterstock
(b) P(survived| not first-class) = P(S|FC) =
= 0.276

17. What Is Conditional Probability?
Calculating Conditional Probabilities
To find the conditional probability P(A | B), use the formula
𝑃 𝐴 𝐵 = 𝑃(𝐴 𝑎𝑛𝑑 𝐵) 𝑃(𝐵) = 𝑃(𝐴 ∩ 𝐵) 𝑃(𝐵) = 𝑃(𝑏𝑜𝑡ℎ 𝑒𝑣𝑒𝑛𝑡𝑠 𝑜𝑐𝑐𝑢𝑟 𝑡𝑜𝑔𝑒𝑡ℎ𝑒𝑟) 𝑃(𝑔𝑖𝑣𝑒𝑛 𝑒𝑣𝑒𝑛𝑡 𝑜𝑐𝑐𝑢𝑟𝑠)

18. What Is Conditional Probability?
Calculating Conditional Probabilities
To find the conditional probability P(A | B), use the formula
𝑃 𝐴 𝐵 = 𝑃(𝐴 𝑎𝑛𝑑 𝐵) 𝑃(𝐵) = 𝑃(𝐴 ∩ 𝐵) 𝑃(𝐵) = 𝑃(𝑏𝑜𝑡ℎ 𝑒𝑣𝑒𝑛𝑡𝑠 𝑜𝑐𝑐𝑢𝑟 𝑡𝑜𝑔𝑒𝑡ℎ𝑒𝑟) 𝑃(𝑔𝑖𝑣𝑒𝑛 𝑒𝑣𝑒𝑛𝑡 𝑜𝑐𝑐𝑢𝑟𝑠)
The choice of which event is A and which is B is arbitrary, so it is also true that:

19. What Is Conditional Probability?
Calculating Conditional Probabilities
To find the conditional probability P(A | B), use the formula
𝑃 𝐴 𝐵 = 𝑃(𝐴 𝑎𝑛𝑑 𝐵) 𝑃(𝐵) = 𝑃(𝐴 ∩ 𝐵) 𝑃(𝐵) = 𝑃(𝑏𝑜𝑡ℎ 𝑒𝑣𝑒𝑛𝑡𝑠 𝑜𝑐𝑐𝑢𝑟 𝑡𝑜𝑔𝑒𝑡ℎ𝑒𝑟) 𝑃(𝑔𝑖𝑣𝑒𝑛 𝑒𝑣𝑒𝑛𝑡 𝑜𝑐𝑐𝑢𝑟𝑠)
The choice of which event is A and which is B is arbitrary, so it is also true that:
𝑃 𝐵 𝐴 = 𝑃(𝐵 𝑎𝑛𝑑 𝐴) 𝑃(𝐴) = 𝑃(𝐵 ∩𝐴) 𝑃(𝐴)

20. What Is Conditional Probability?
Problem: A survey of all residents in a large apartment complex reveals
that 68% use Facebook, 28% use Instagram, and 25% do both. Suppose
we select a resident at random. Given that the person uses Facebook,
what’s the probability that she or he uses Instagram?
Ann Heath

21. What Is Conditional Probability?
Problem: A survey of all residents in a large apartment complex reveals
that 68% use Facebook, 28% use Instagram, and 25% do both. Suppose
we select a resident at random. Given that the person uses Facebook,
what’s the probability that she or he uses Instagram?
Ann Heath
P(Instagram | Facebook) = P(I | F)
= 𝑃(𝐼|𝐹) 𝑃(𝐹) =
= 0.368

22. Conditional Probability and Independence
A and B are independent events if knowing whether or not one event has
occurred does not change the probability that the other event will happen. In other words, events A and B are independent if
P(A|B) = P(A|BC) = P(A)
Alternatively, events A and B are independent if
P(B|A) = P(B|AC) = P(B)

23. Conditional Probability and Independence
A and B are independent events if knowing whether or not one event has
occurred does not change the probability that the other event will happen. In other words, events A and B are independent if
P(A|B) = P(A|BC) = P(A)
Alternatively, events A and B are independent if
P(B|A) = P(B|AC) = P(B)
P(pierced ear|male) = P(B|A) = 19/90 = 0.211

24. Conditional Probability and Independence
A and B are independent events if knowing whether or not one event has
occurred does not change the probability that the other event will happen. In other words, events A and B are independent if
P(A|B) = P(A|BC) = P(A)
Alternatively, events A and B are independent if
P(B|A) = P(B|AC) = P(B)
P(pierced ear|male) = P(B|A) = 19/90 = 0.211
P(pierced ear|female) = P(B|AC) = 84/88 = 0.579

25. Conditional Probability and Independence
A and B are independent events if knowing whether or not one event has
occurred does not change the probability that the other event will happen. In other words, events A and B are independent if
P(A|B) = P(A|BC) = P(A)
Alternatively, events A and B are independent if
P(B|A) = P(B|AC) = P(B)
P(pierced ear|male) = P(B|A) = 19/90 = 0.211
P(pierced ear|female) = P(B|AC) = 84/88 = 0.579
Knowing that the chosen student is a male changes (greatly reduces) the probability that the student has a pierced ear.
So these two events are not independent.

26. Conditional Probability and Independence
Problem: Is there a relationship between gender and handedness? To find out, we used Census At School’s Random Data Selector to choose an SRS of 100 Australian high school students who completed a survey. The two-way table summarizes the relationship between gender and dominant hand for these students. Suppose we choose one of the students in the sample at random. Are the events “male” and “left-handed” independent? Justify your answer.
Graeme Harris/Getty Images

27. Conditional Probability and Independence
Problem: Is there a relationship between gender and handedness? To find out, we used Census At School’s Random Data Selector to choose an SRS of 100 Australian high school students who completed a survey. The two-way table summarizes the relationship between gender and dominant hand for these students. Suppose we choose one of the students in the sample at random. Are the events “male” and “left-handed” independent? Justify your answer.
Graeme Harris/Getty Images
P(left-handed | male) = 7/46 = 0.152
P(left-handed | female) = 3/54 = 0.056

28. Conditional Probability and Independence
Problem: Is there a relationship between gender and handedness? To find out, we used Census At School’s Random Data Selector to choose an SRS of 100 Australian high school students who completed a survey. The two-way table summarizes the relationship between gender and dominant hand for these students. Suppose we choose one of the students in the sample at random. Are the events “male” and “left-handed” independent? Justify your answer.
Graeme Harris/Getty Images
P(left-handed | male) = 7/46 = 0.152
P(left-handed | female) = 3/54 = 0.056
Because these probabilities are not equal, the events “male” and “left-handed” are not independent. Knowing that the student is male increases the probability that the student is left-handed.

29. The General Multiplication Rule
About 55% of high school students participate in a school athletic team.

30. The General Multiplication Rule
About 55% of high school students participate in a school athletic team.
Roughly 6% of these athletes go on to play on a college team in the NCAA.

31. The General Multiplication Rule
About 55% of high school students participate in a school athletic team.
Roughly 6% of these athletes go on to play on a college team in the NCAA.
What percent of high school students play a sport in high school and go on to play on an NCAA team?

32. The General Multiplication Rule
About 55% of high school students participate in a school athletic team.
Roughly 6% of these athletes go on to play on a college team in the NCAA.
What percent of high school students play a sport in high school and go on to play on an NCAA team?
About 6% of 55%, or roughly 3.3%.

33. The General Multiplication Rule
P(high school sport and NCAA team)
= P(high school sport) · P(NCAA team | high school sport)
= (0.55)(0.06)
= 0.033

34. The General Multiplication Rule
P(high school sport and NCAA team)
= P(high school sport) · P(NCAA team | high school sport)
= (0.55)(0.06)
= 0.033
For any chance process, the probability that events A and B both occur can be found using the general multiplication rule:
P(A and B) = P(A ∩ B) = P(A) · P (B|A)

35. The General Multiplication Rule
Problem: The Pew Internet and American Life Project reported that 79% of teenagers (ages 13 to 17) use social media, and that 39% of teens who use social media feel pressure to post content that will be popular and get lots of comments or likes. Find the probability that a randomly selected teen uses social media and feels pressure to post content that will be popular and get lots of comments or likes.
Ann Heath

36. The General Multiplication Rule
Problem: The Pew Internet and American Life Project reported that 79% of teenagers (ages 13 to 17) use social media, and that 39% of teens who use social media feel pressure to post content that will be popular and get lots of comments or likes. Find the probability that a randomly selected teen uses social media and feels pressure to post content that will be popular and get lots of comments or likes.
Ann Heath
P(use social media and feel pressure)
= P(use social media) · P(feel pressure|use social media)
= (0.79)(0.39)
= 0.308

37. Tree Diagrams and Conditional Probability
A tree diagram shows the sample space of a chance process involving
multiple stages. The probability of each outcome is shown on the
corresponding branch of the tree. All probabilities after the first stage are
conditional probabilities.

38. Tree Diagrams and Conditional Probability
A tree diagram shows the sample space of a chance process involving
multiple stages. The probability of each outcome is shown on the
corresponding branch of the tree. All probabilities after the first stage are
conditional probabilities.

39. Tree Diagrams and Conditional Probability
Problem: Recently, Harris Interactive reported that 20% of millennials, 25% of Gen Xers, 21% of baby boomers, and 17% of matures (age 68 and older) read more ebooks than print books. According to the U.S. Census Bureau, 34% of those 18 and over are millennials, 22% are Gen Xers, 30% are baby boomers, and 14% are matures. Suppose we select one U.S. adult at random and record which generation the person is from and whether she or he reads more ebooks or print books.
(a) Draw a tree diagram to model this chance process.
Burlingham/Shuterstock.com

40. Tree Diagrams and Conditional Probability
Problem: Recently, Harris Interactive reported that 20% of millennials, 25% of Gen Xers, 21% of baby boomers, and 17% of matures (age 68 and older) read more ebooks than print books. According to the U.S. Census Bureau, 34% of those 18 and over are millennials, 22% are Gen Xers, 30% are baby boomers, and 14% are matures. Suppose we select one U.S. adult at random and record which generation the person is from and whether she or he reads more ebooks or print books.
(a) Draw a tree diagram to model this chance process.
(a)
Burlingham/Shuterstock.com

41. Tree Diagrams and Conditional Probability
Problem:
(b) Find the probability that the person reads more ebooks than print books.

42. Tree Diagrams and Conditional Probability
Problem:
(b) Find the probability that the person reads more ebooks than print books.

43. Tree Diagrams and Conditional Probability
Problem:
(b) Find the probability that the person reads more ebooks than print books.
(b) P(reads more ebooks)
= (0.34)(0.20) + (0.22)(0.25) + (0.30)(0.21) + (0.14)(0.17) = =

44. Tree Diagrams and Conditional Probability
Problem:
(c) Suppose the chosen person reads more ebooks than print books. What’s the probability that she or he is a millennial?

45. Tree Diagrams and Conditional Probability
Problem:
(c) Suppose the chosen person reads more ebooks than print books. What’s the probability that she or he is a millennial?
(c) P(millennial | reads more ebooks)
= 𝑃(𝑚𝑖𝑙𝑙𝑒𝑛𝑖𝑎𝑙 𝑎𝑛𝑑 𝑟𝑒𝑎𝑑𝑠 𝑚𝑜𝑟𝑒 𝑒𝑏𝑜𝑜𝑘𝑠) 𝑃(𝑟𝑒𝑎𝑑𝑠 𝑚𝑜𝑟𝑒 𝑒𝑏𝑜𝑜𝑘𝑠) = =

46. The Multiplication Rule for Independent Events
When events A and B are independent, P(B|A) = P(B).

47. The Multiplication Rule for Independent Events
When events A and B are independent, P(B|A) = P(B).
We can simplify the general multiplication rule as follows:

48. The Multiplication Rule for Independent Events
When events A and B are independent, P(B|A) = P(B).
We can simplify the general multiplication rule as follows:
P(A and B) = P(A ∩ B) = P(A) · P(B|A)
= P(A) · P(B)

49. The Multiplication Rule for Independent Events
When events A and B are independent, P(B|A) = P(B).
We can simplify the general multiplication rule as follows:
P(A and B) = P(A ∩ B) = P(A) · P(B|A)
= P(A) · P(B)
If A and B are independent events, the probability that A and B both occur is P(A and B) = P (A ∩ B) = P(A) · P(B)

50. The Multiplication Rule for Independent Events
When events A and B are independent, P(B|A) = P(B).
We can simplify the general multiplication rule as follows:
P(A and B) = P(A ∩ B) = P(A) · P(B|A)
= P(A) · P(B)
If A and B are independent events, the probability that A and B both occur is P(A and B) = P (A ∩ B) = P(A) · P(B)
CAUTION:
Note that this rule applies only to independent events.

51. The Multiplication Rule for Independent Events
Problem: Many people who visit clinics to be tested for HIV, the virus that causes AIDS, don’t come back to learn their test results. Clinics now use “rapid HIV tests” that give a result while the client waits. In a clinic in Malawi, for example, use of rapid tests increased the percentage of clients who learned their test results
from 69% to over 99%. The trade-off for fast results is that rapid tests are less accurate than slower laboratory tests. Applied to people who have no HIV antibodies, one rapid test has a probability of about of producing a false positive (i.e., of falsely indicating that antibodies are present). If a clinic tests 200 randomly selected people who are free of HIV antibodies, what is the probability that at least one false positive will occur? Assume that test results for different individuals are independent.

52. The Multiplication Rule for Independent Events
Problem: Many people who visit clinics to be tested for HIV, the virus that causes AIDS, don’t come back to learn their test results. Clinics now use “rapid HIV tests” that give a result while the client waits. In a clinic in Malawi, for example, use of rapid tests increased the percentage of clients who learned their test results
from 69% to over 99%. The trade-off for fast results is that rapid tests are less accurate than slower laboratory tests. Applied to people who have no HIV antibodies, one rapid test has a probability of about of producing a false positive (i.e., of falsely indicating that antibodies are present). If a clinic tests 200 randomly selected people who are free of HIV antibodies, what is the probability that at least one false positive will occur? Assume that test results for different individuals are independent.
P(no false positives) =

53. The Multiplication Rule for Independent Events
Problem: Many people who visit clinics to be tested for HIV, the virus that causes AIDS, don’t come back to learn their test results. Clinics now use “rapid HIV tests” that give a result while the client waits. In a clinic in Malawi, for example, use of rapid tests increased the percentage of clients who learned their test results
from 69% to over 99%. The trade-off for fast results is that rapid tests are less accurate than slower laboratory tests. Applied to people who have no HIV antibodies, one rapid test has a probability of about of producing a false positive (i.e., of falsely indicating that antibodies are present). If a clinic tests 200 randomly selected people who are free of HIV antibodies, what is the probability that at least one false positive will occur? Assume that test results for different individuals are independent.
P(no false positives) = P(all 200 tests negative)

54. The Multiplication Rule for Independent Events
Problem: Many people who visit clinics to be tested for HIV, the virus that causes AIDS, don’t come back to learn their test results. Clinics now use “rapid HIV tests” that give a result while the client waits. In a clinic in Malawi, for example, use of rapid tests increased the percentage of clients who learned their test results
from 69% to over 99%. The trade-off for fast results is that rapid tests are less accurate than slower laboratory tests. Applied to people who have no HIV antibodies, one rapid test has a probability of about of producing a false positive (i.e., of falsely indicating that antibodies are present). If a clinic tests 200 randomly selected people who are free of HIV antibodies, what is the probability that at least one false positive will occur? Assume that test results for different individuals are independent.
P(no false positives) = P(all 200 tests negative)
= (0.996)(0.996) ··· (0.996)

55. The Multiplication Rule for Independent Events
Problem: Many people who visit clinics to be tested for HIV, the virus that causes AIDS, don’t come back to learn their test results. Clinics now use “rapid HIV tests” that give a result while the client waits. In a clinic in Malawi, for example, use of rapid tests increased the percentage of clients who learned their test results
from 69% to over 99%. The trade-off for fast results is that rapid tests are less accurate than slower laboratory tests. Applied to people who have no HIV antibodies, one rapid test has a probability of about of producing a false positive (i.e., of falsely indicating that antibodies are present). If a clinic tests 200 randomly selected people who are free of HIV antibodies, what is the probability that at least one false positive will occur? Assume that test results for different individuals are independent.
P(no false positives) = P(all 200 tests negative)
= (0.996)(0.996) ··· (0.996) =

56. The Multiplication Rule for Independent Events
Problem: Many people who visit clinics to be tested for HIV, the virus that causes AIDS, don’t come back to learn their test results. Clinics now use “rapid HIV tests” that give a result while the client waits. In a clinic in Malawi, for example, use of rapid tests increased the percentage of clients who learned their test results
from 69% to over 99%. The trade-off for fast results is that rapid tests are less accurate than slower laboratory tests. Applied to people who have no HIV antibodies, one rapid test has a probability of about of producing a false positive (i.e., of falsely indicating that antibodies are present). If a clinic tests 200 randomly selected people who are free of HIV antibodies, what is the probability that at least one false positive will occur? Assume that test results for different individuals are independent.
P(no false positives) = P(all 200 tests negative)
= (0.996)(0.996) ··· (0.996) = =

57. The Multiplication Rule for Independent Events
Problem: Many people who visit clinics to be tested for HIV, the virus that causes AIDS, don’t come back to learn their test results. Clinics now use “rapid HIV tests” that give a result while the client waits. In a clinic in Malawi, for example, use of rapid tests increased the percentage of clients who learned their test results
from 69% to over 99%. The trade-off for fast results is that rapid tests are less accurate than slower laboratory tests. Applied to people who have no HIV antibodies, one rapid test has a probability of about of producing a false positive (i.e., of falsely indicating that antibodies are present). If a clinic tests 200 randomly selected people who are free of HIV antibodies, what is the probability that at least one false positive will occur? Assume that test results for different individuals are independent.
P(no false positives) = P(all 200 tests negative)
= (0.996)(0.996) ··· (0.996) = =
P(at least one false positive) = 1 – =

58. Section Summary CALCULATE and INTERPRET conditional probabilities.
DETERMINE if two events are independent.
USE the general multiplication rule to CALCULATE probabilities.
USE a tree diagram to model a chance process involving a sequence of outcomes and to CALCULATE probabilities.
When appropriate, USE the multiplication rule for independent events to CALCULATE probabilities.

59. Assignment
5.3 p #62-94 EOE and all (62, 66, 70, 74, 78, 82, 86, 90, 94, all) If you are stuck on any of these, look at the odd before or after and the answer in the back of your book. If you are still not sure text a friend or me for help (before 8pm). Tomorrow we will check homework and review for 5.3 Quiz.