Chapter Five
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Chapter Five. A Survey of Probability Concepts. GOALS When you have completed this chapter, you will be able to:. ONE Define probability. TWO Describe the classical, empirical, and subjective approaches to probability.

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Chapter Five

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Chapter five

Chapter Five

A Survey of Probability Concepts

GOALS

When you have completed this chapter, you will be able to:

ONEDefine probability.

TWODescribe the classical, empirical, and subjective approaches to probability.

THREEUnderstand the terms: experiment, event, outcome, permutations, and combinations.


Chapter five

Chapter Five continued

A Survey of Probability Concepts

GOALS

When you have completed this chapter, you will be able to:

FOURDefine the terms: conditional probability and joint probability.

FIVECalculate probabilities applying the rules of addition and the rules of multiplication.

SIXUse a tree diagram to organize and compute probabilities.


Chapter five

Chapter Five continued

A Survey of Probability Concepts

SEVENCalculate a probability using Bayes’ theorem.


Chapter five

There are three definitions of probability: classical, empirical, and subjective.

Subjectiveprobability is based on whatever information is available.

The Classical definition applies when there are n equally likely outcomes.

The Empirical definition applies when the number of times the event happens is divided by the number of observations.


Chapter five

An Outcome is the particular result of an experiment.

Experiment: A fair die is cast.

Possible outcomes: The numbers 1, 2, 3, 4, 5, 6

An Event is the collection of one or more outcomes of an experiment.

One possible event: The occurrence of an even number. That is, we collect the outcomes 2, 4, and 6.


Chapter five

Events are Mutually Exclusive if the occurrence of any one event means that none of the others can occur at the same time.

Events are Independent if the occurrence of one event does not affect the occurrence of another.

Independence: Rolling a 2 on the first throw does not influence the probability of a 3 on the next throw. It is still a one in 6 chance.

Mutually exclusive: Rolling a 2 precludes rolling a 1, 3, 4, 5, 6 on the same roll.


Chapter five

Events are Collectively Exhaustive if at least one of the events must occur when an experiment is conducted.


Chapter five

This is an example of the empirical definition of probability.

  • To find the probability a selected student earned an A:

Throughout her teaching career Professor Jones has awarded 186 A’s out of 1,200 students. What is the probability that a student in her section this semester will receive an A?


Chapter five

Examples of subjective probability are:

estimating the probability the Buffalo Bills will win the Super Bowl this year.

estimating the probability mortgage rates for home loans will top 8 percent.


Chapter five

If two events

A and B are mutually exclusive, the

Special Rule of Addition states that the

Probability of A or B occurring equals the sum of their respective probabilities.

P(A or B) = P(A) + P(B)


Chapter five

Lynchburg Commuter Airways recently supplied the following information on their commuter flights from Lynchburg to Bedford:


Chapter five

If A is the event that a flight arrives early, then P(A) = 100/1000 = .10.

If B is the event that a flight arrives late, then P(B) = 75/1000 = .075.

The probability that a flight is either early or late is:

P(A or B) = P(A) + P(B) = .10 + .075 =.175.


Chapter five

The Complement Rule is used to determine the probability of an event occurring by subtracting the probability of the event not occurring from 1.

If P(A) is the probability of event A and P(~A) is the complement of A,

P(A) + P(~A) = 1 or P(A) = 1 - P(~A).


Chapter five

A Venn Diagram illustrating the complement rule would appear as:

A

~A


Chapter five

Recall example 3. Use the complement rule to find the probability of an early (A) or a late (B) flight

If C is the event that a flight arrives on time, then P(C) = 800/1000 = .8.

If D is the event that a flight is canceled, then

P(D) = 25/1000 = .025.


Chapter five

P(A or B) = 1 - P(C or D)

= 1 - [.8 +.025]

=.175

D

.025

C

.8

~(C or D) = (A or B)

.175


Chapter five

If A and B are two events that are not mutually exclusive, then P(A or B) is given by the following formula:

P(A or B) = P(A) + P(B) - P(A and B)


Chapter five

The Venn Diagram illustrates this rule:

B

A and B

A


Chapter five

In a sample of 500 students, 320 said they had a stereo, 175 said they had a TV, and 100 said they had both. 5 said they had neither.

TV

175

Both

100

Stereo

320


Chapter five

If a student is selected at random, what is the probability that the student has only a stereo or TV? What is the probability that the student has both a stereo and TV?

P(S or TV) = P(S) + P(TV) - P(S and TV)

= 320/500 + 175/500 – 100/500

= .79.

P(S and TV) = 100/500

= .20


Chapter five

A Joint Probability measures the likelihood that two or more events will happen concurrently.

An example would be the event that a student has both a stereo and TV in his or her dorm room.


Chapter five

The Special Rule of Multiplication requires that two events A and B are independent.

  • Two events A and B are independentif the occurrence of one has no effect on the probability of the occurrence of the other.

  • This rule is written: P(A and B) = P(A)P(B)


Chapter five

Chris owns two stocks, IBM and General Electric (GE). The probability that IBM stock will increase in value next year is .5 and the probability that GE stock will increase in value next year is .7. Assume the two stocks are independent. What is the probability that both stocks will increase in value next year?

P(IBM and GE) = (.5)(.7) = .35


Chapter five

P(at least one)

= P(IBM but not GE)

+ P(GE but not IBM)

+ P(IBM and GE)

(.5)(1-.7)

+ (.7)(1-.5)

+ (.7)(.5)

= .85


Chapter five

A Conditional Probability is the probability of a particular event occurring, given that another event has occurred.

The probability of event A occurring given that the event B has occurred is written P(A|B).


Chapter five

The General Rule of Multiplication is used to find the joint probability that two events will occur.

It states that for two events A and B, the joint probability that both events will happen is found by multiplying the probability that event A will happen by the conditional probability of B given that A has occurred.


Chapter five

The joint probability,

P(A and B), is given by the following formula:

P(A and B) = P(A)P(B/A) or P(A and B) = P(B)P(A/B)


Chapter five

The Dean of the School of Business at Owens University collected the following information about undergraduate students in her college:


Chapter five

If a student is selected at random, what is the probability that the student is a female (F) accounting major (A)?

P(A and F) = 110/1000.

Given that the student is a female, what is the probability that she is an accounting major?

P(A|F) = P(A and F)/P(F)

= [110/1000]/[400/1000] = .275


Chapter five

A Tree Diagram is useful for portraying conditional and joint probabilities. It is particularly useful for analyzing business decisions involving several stages.

  • Example 8: In a bag containing 7 red chips and 5 blue chips you select 2 chips one after the other without replacement. Construct a tree diagram showing this information.


Chapter five

6/11

R2

R1

7/12

B2

5/11

R2

7/11

B1

5/12

4/11

B2


Chapter five

Bayes’ Theorem is a method for revising a probability given additional information.

It is computed using the following formula:


Chapter five

Duff Cola Company recently received several complaints that their bottles are under-filled. A complaint was received today but the production manager is unable to identify which of the two Springfield plants (A or B) filled this bottle. What is the probability that the under-filled bottle came from plant A?


Chapter five

The following table summarizes the Duff production experience.


Chapter five

The likelihood the bottle was filled in Plant A is reduced from .55 to .4783.


Chapter five

The Multiplication Formula indicates that if there are m ways of doing one thing and n ways of doing another thing, there are m xn ways of doing both.

Example 10: Dr. Delong has 10 shirts and 8 ties. How many shirt and tie outfits does he have?

(10)(8) = 80


Chapter five

A Permutation is any arrangement of r objects selected from n possible objects.

Note: The order of arrangement is important in permutations.


Chapter five

ACombination is the number of ways to choose r objects from a group of n objects without regard to order.


Chapter five

There are 12 players on the Carolina Forest High School basketball team. Coach Thompson must pick five players among the twelve on the team to comprise the starting lineup. How many different groups are possible?(Order does not matter.)


Chapter five

Suppose that in addition to selecting the group, he must also rank each of the players in that starting lineup according to their ability (order matters).


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