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Bluman, Chapter 4 4.2 Addition Rules for Probability Two events are mutually exclusive events if they cannot occur at the same time (i.e., they have no outcomes in common) 1 Friday, January 25, 13

4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

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Page 1: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

4.2 Addition Rules for Probability Two events are mutually exclusive

events if they cannot occur at the same time (i.e., they have no outcomes in common)

1Friday, January 25, 13

Page 2: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Chapter 4Probability and Counting Rules

Section 4-2Example 4-15Page #200

2

2Friday, January 25, 13

Page 3: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-15: Rolling a Die

3

3Friday, January 25, 13

Page 4: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-15: Rolling a DieDetermine which events are mutually exclusive and which are not, when a single die is rolled.

a. Getting an odd number and getting an even number

Getting an odd number: 1, 3, or 5Getting an even number: 2, 4, or 6

Mutually Exclusive

3

3Friday, January 25, 13

Page 5: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-15: Rolling a Die

4

4Friday, January 25, 13

Page 6: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-15: Rolling a DieDetermine which events are mutually exclusive and which are not, when a single die is rolled.

b. Getting a 3 and getting an odd number

Getting a 3: 3Getting an odd number: 1, 3, or 5

Not Mutually Exclusive

4

4Friday, January 25, 13

Page 7: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-15: Rolling a Die

5

5Friday, January 25, 13

Page 8: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-15: Rolling a DieDetermine which events are mutually exclusive and which are not, when a single die is rolled.

c. Getting an odd number and getting a number less than 4

Getting an odd number: 1, 3, or 5Getting a number less than 4: 1, 2, or 3

Not Mutually Exclusive

5

5Friday, January 25, 13

Page 9: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-15: Rolling a Die

6

6Friday, January 25, 13

Page 10: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-15: Rolling a DieDetermine which events are mutually exclusive and which are not, when a single die is rolled.

d. Getting a number greater than 4 and getting a number less than 4

Getting a number greater than 4: 5 or 6Getting a number less than 4: 1, 2, or 3

Mutually Exclusive

6

6Friday, January 25, 13

Page 11: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Chapter 4Probability and Counting Rules

Section 4-2Example 4-18Page #201

7

7Friday, January 25, 13

Page 12: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-18: Political Affiliation

8

8Friday, January 25, 13

Page 13: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-18: Political AffiliationAt a political rally, there are 20 Republicans, 13 Democrats, and 6 Independents. If a person is selected at random, find the probability that he or she is either a Democrat or an Republican.

Mutually Exclusive Events

8

8Friday, January 25, 13

Page 14: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-18: Political AffiliationAt a political rally, there are 20 Republicans, 13 Democrats, and 6 Independents. If a person is selected at random, find the probability that he or she is either a Democrat or an Republican.

Mutually Exclusive Events

8

8Friday, January 25, 13

Page 15: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-18: Political AffiliationAt a political rally, there are 20 Republicans, 13 Democrats, and 6 Independents. If a person is selected at random, find the probability that he or she is either a Democrat or an Republican.

Mutually Exclusive Events

8

8Friday, January 25, 13

Page 16: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Chapter 4Probability and Counting Rules

Section 4-2Example 4-21Page #202

9

9Friday, January 25, 13

Page 17: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-21: Medical StaffIn a hospital unit there are 8 nurses and 5 physicians; 7 nurses and 3 physicians are females.If a staff person is selected, find the probability that the subject is a nurse or a male.

10

10Friday, January 25, 13

Page 18: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Staff Females Males TotalNursesPhysicians

Example 4-21: Medical StaffIn a hospital unit there are 8 nurses and 5 physicians; 7 nurses and 3 physicians are females.If a staff person is selected, find the probability that the subject is a nurse or a male.

10

10Friday, January 25, 13

Page 19: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Staff Females Males TotalNursesPhysicians

85

Example 4-21: Medical StaffIn a hospital unit there are 8 nurses and 5 physicians; 7 nurses and 3 physicians are females.If a staff person is selected, find the probability that the subject is a nurse or a male.

10

10Friday, January 25, 13

Page 20: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Staff Females Males TotalNursesPhysicians

85

Example 4-21: Medical StaffIn a hospital unit there are 8 nurses and 5 physicians; 7 nurses and 3 physicians are females.If a staff person is selected, find the probability that the subject is a nurse or a male.

10

73

10Friday, January 25, 13

Page 21: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Staff Females Males TotalNursesPhysicians

85

Example 4-21: Medical StaffIn a hospital unit there are 8 nurses and 5 physicians; 7 nurses and 3 physicians are females.If a staff person is selected, find the probability that the subject is a nurse or a male.

10

7 13 2

10Friday, January 25, 13

Page 22: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Staff Females Males TotalNursesPhysicians

85

Example 4-21: Medical StaffIn a hospital unit there are 8 nurses and 5 physicians; 7 nurses and 3 physicians are females.If a staff person is selected, find the probability that the subject is a nurse or a male.

10

7 13 2

Total

10Friday, January 25, 13

Page 23: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Staff Females Males TotalNursesPhysicians

85

Example 4-21: Medical StaffIn a hospital unit there are 8 nurses and 5 physicians; 7 nurses and 3 physicians are females.If a staff person is selected, find the probability that the subject is a nurse or a male.

10

7 13 2

Total 10 3 13

10Friday, January 25, 13

Page 24: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Staff Females Males TotalNursesPhysicians

85

Example 4-21: Medical StaffIn a hospital unit there are 8 nurses and 5 physicians; 7 nurses and 3 physicians are females.If a staff person is selected, find the probability that the subject is a nurse or a male.

10

7 13 2

Total 10 3 13

10Friday, January 25, 13

Page 25: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Staff Females Males TotalNursesPhysicians

85

Example 4-21: Medical StaffIn a hospital unit there are 8 nurses and 5 physicians; 7 nurses and 3 physicians are females.If a staff person is selected, find the probability that the subject is a nurse or a male.

10

7 13 2

Total 10 3 13

10Friday, January 25, 13

Page 26: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Example 4-22

On New Year’s Eve, the probability of a person driving while intoxicated is 0.32, the probability of a person having a driving accident is 0.09, and the probability of a person having a driving accident while intoxicated is 0.06. What is the probability of a person driving while intoxicated or having a driving accident?

11Friday, January 25, 13

Page 27: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Non mutually exclusive Venn diagram.

12Friday, January 25, 13

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Bluman, Chapter 4

Mutually Exclusive Diagram

A B

13Friday, January 25, 13

Page 29: 4.2 Addition Rules for Probability - navimath · 2013-01-26 · Probability and Counting Rules Section 4-2 Example 4-21 Page #202 9 Friday, January 25, 13 9. Bluman, Chapter 4 Example

Bluman, Chapter 4

Homework

Section 4.2 APPYLING CONCEPTS

PAGE 203 Page 204-206, #1-25 oddsDue Tuesday 16, 2012

14Friday, January 25, 13