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For customers purchasing a refrigerator at a certain appliance store, let A be the event that the refrigerator was manufactured in the U.S., B be the event that the refrigerator had an icemaker, and C be the event that the customer purchased an extended warranty. Relevant probabilities are

\(\begin{aligned}{\rm{P(A) = }}{\rm{.75}}\;\;\;{\rm{P(B}}\mid {\rm{A) = }}{\rm{.9}}\;\;\;{\rm{P}}\left( {{\rm{B}}\mid {{\rm{A}}^{\rm{\cent}}}} \right){\rm{ = }}{\rm{.8}}\\{\rm{P(C}}\mid {\rm{A\c{C}B) = }}{\rm{.8}}\;\;\;{\rm{P}}\left( {{\rm{C}}\mid {\rm{A\c{C}}}{{\rm{B}}^{\rm{\cent}}}} \right){\rm{ = }}{\rm{.6}}\\{\rm{P}}\left( {{\rm{C}}\mid {{\rm{A}}^{\rm{\cent}}}{\rm{\c{C}B}}} \right){\rm{ = }}{\rm{.7}}\;\;\;{\rm{P}}\left( {{\rm{C}}\mid {{\rm{A}}^{\rm{\cent}}}{\rm{\c{C}}}{{\rm{B}}^{\rm{\cent}}}} \right){\rm{ = }}{\rm{.3}}\end{aligned}\)

Construct a tree diagram consisting of first-, second-, and third-generation branches, and place an event label and appropriate probability next to each branch. b. Compute \({\rm{P(A\c{C}B\c{C}C)}}\). c. Compute \({\rm{P(B\c{C}C)}}\). d. Compute \({\rm{P(C)}}\). e. Compute \({\rm{P(A}}\mid {\rm{B\c{C}C)}}\), the probability of a U.S. purchase given that an icemaker and extended warranty are also purchased

Short Answer

Expert verified

a. Tree diagram given below

b.\(P(A\c{C}B\c{C}C) = 0.54\)

c.\(P(B\c{C}C) = 0.68\)

d.\(P(C) = 0.74\)

e. \(P(A\mid B\c{C}C) = 0.7941\)

Step by step solution

01

Determine first and second layer probabilities

(a): The Tree Diagram:

The tree diagram which represents the experimental situation given in the exercise is given below.

The initial branches represent the first layer of events, and the adequate probabilities are given in the diagram. Second-generation branches represent the second layer of events, with the adequate conditional probabilities given. The third-generation branches represent the third layer of events, with adequate conditional probabilities given.

We are given relevant probabilities which we are going to use.

First layer probabilities:

\(\begin{aligned}{\rm{P(A) = 0}}{\rm{.75}}\\{\rm{P}}\left( {{{\rm{A}}^{\rm{\cent}}}} \right){\rm{ = 1 - P(A)}}\\{\rm{ = 0}}{\rm{.25}}\end{aligned}\)

Second layer probabilities are

\(\begin{aligned}{\rm{P(B}}\mid {\rm{A) = 0}}{\rm{.9}}\\{\rm{P}}\left( {{{\rm{B}}^{\rm{\cent}}}\mid {\rm{A}}} \right){\rm{ = 1 - P(B}}\mid {\rm{A)}}\\{\rm{ = 0}}{\rm{.1P}}\left( {{\rm{B}}\mid {{\rm{A}}^{\rm{\cent}}}} \right)\\{\rm{ = 0}}{\rm{.8P}}\left( {{{\rm{B}}^{\rm{\cent}}}\mid {{\rm{A}}^{\rm{\cent}}}} \right)\\{\rm{ = 1 - P}}\left( {{\rm{B}}\mid {{\rm{A}}^{\rm{\cent}}}} \right)\\{\rm{ = 0}}{\rm{.2}}\end{aligned}\)

02

Determine third layer probabilities

Third layer probabilities are

\(\begin{aligned}{\rm{P(C}}\mid {\rm{A\c{C}B) = 0}}{\rm{.8}}\\{\rm{P}}\left( {{{\rm{C}}^{\rm{\cent}}}\mid {\rm{A\c{C}B}}} \right){\rm{ = 0}}{\rm{.2}}\\{\rm{P}}\left( {{\rm{C}}\mid {\rm{A\c{C}}}{{\rm{B}}^{\rm{\cent}}}} \right){\rm{ = 0}}{\rm{.6}}\\{\rm{P}}\left( {{{\rm{C}}^{\rm{\cent}}}\mid {\rm{A\c{C}}}{{\rm{B}}^{\rm{\cent}}}} \right){\rm{ = 0}}{\rm{.4}}\\{\rm{P}}\left( {{\rm{C}}\mid {{\rm{A}}^{\rm{\cent}}}{\rm{\c{C}B}}} \right){\rm{ = 0}}{\rm{.7}}\\{\rm{P}}\left( {{{\rm{C}}^{\rm{\cent}}}\mid {{\rm{A}}^{\rm{\cent}}}{\rm{\c{C}B}}} \right){\rm{ = 0}}{\rm{.3}}\\{\rm{P}}\left( {{\rm{C}}\mid {{\rm{A}}^{\rm{\cent}}}{\rm{\c{C}}}{{\rm{B}}^{\rm{\cent}}}} \right){\rm{ = 0}}{\rm{.3}}\\{\rm{P}}\left( {{{\rm{C}}^{\rm{\cent}}}\mid {{\rm{A}}^{\rm{\cent}}}{\rm{\c{C}}}{{\rm{B}}^{\rm{\cent}}}} \right){\rm{ = 0}}{\rm{.7}}\end{aligned}\)

At the event of the third-generation branches, there are the probability of the intersection of adequate three events that lead to that point, however, we are not supposed to do that now (see description of (a)).

03

Determine the value using multiplication rule

(b):

The Multiplication Rule

\({\rm{P(A\c{C}B) = P(A}}\mid {\rm{B)*P(B)}}\)

Using the multiplication rule twice, we have

\(\begin{aligned}{\rm{P(A\c{C}B\c{C}C) = P(C}}\mid {\rm{A\c{C}B)*P(A\c{C}B)}}\\{\rm{ = P(C}}\mid {\rm{A\c{C}B)*P(B}}\mid {\rm{A)*P(A)}}\\{\rm{ = 0}}{\rm{.75*0}}{\rm{.9*0}}{\rm{.8}}\\{\rm{ = 0}}{\rm{.54}}\end{aligned}\)

04

Determine the value using multiplication rule twice

(c):

For any events \({{\rm{D}}_{\rm{1}}}\), \({{\rm{D}}_{\rm{2}}}\), and \({{\rm{D}}_{\rm{3}}}\), we have that

\(\left. {{{\rm{D}}_{\rm{1}}}{\rm{\c{C}}}{{\rm{D}}_{\rm{2}}}{\rm{\c{C}}}{{\rm{D}}_{\rm{3}}}} \right){\rm{ + }}\left( {{{\rm{D}}_{\rm{1}}}{\rm{\c{C}}}{{\rm{D}}_{\rm{2}}}{\rm{\c{C}D}}_{\rm{3}}^{\rm{\cent}}} \right)\)

where " \({\rm{ + }}\) " stands for disjoint union of two events. Using this we have

  1. \(\begin{aligned}{\rm{P(B\c{C}C) = P(B\c{C}C\c{C}A) + P}}\left( {{\rm{B\c{C}C\c{C}}}{{\rm{A}}^{\rm{\cent}}}} \right)\\\mathop {\rm{ = }}\limits^{{\rm{(1)}}} {\rm{0}}{\rm{.54 + 0}}{\rm{.25*0}}{\rm{.8*0}}{\rm{.7}}\\{\rm{ = 0}}{\rm{.68,}}\end{aligned}\)
  2. we compute the probabilities the same way as in (a), by using two times the multiplication rule (or a general theorem of the multiplication rule).
05

Determine the value of \({\rm{P(C)}}\)

(d):

Similarly, as in (b) the following is true

\(\begin{aligned}{\rm{P(C) = P(A\c{C}B\c{C}C) + P}}\left( {{{\rm{A}}^{\rm{\cent}}}{\rm{\c{C}B\c{C}C}}} \right){\rm{ + P}}\left( {{\rm{A\c{C}}}{{\rm{B}}^{\rm{\cent}}}{\rm{\c{C}C}}} \right){\rm{ + P}}\left( {{{\rm{A}}^{\rm{\cent}}}{\rm{\c{C}}}{{\rm{B}}^{\rm{\cent}}}{\rm{\c{C}C}}} \right)\\{\rm{ = 0}}{\rm{.75*0}}{\rm{.9*0}}{\rm{.8 + 0}}{\rm{.75*0}}{\rm{.1*0}}{\rm{.6 + 0}}{\rm{.25*0}}{\rm{.8 \times 0}}{\rm{.7 + 0}}{\rm{.25*0}}{\rm{.2*0}}{\rm{.3}}\\{\rm{ = 0}}{\rm{.54 + 0}}{\rm{.45 + 0}}{\rm{.14 + 0}}{\rm{.015}}\\{\rm{ = 0}}{\rm{.74}}\end{aligned}\)

06

Determine the value of \({\rm{P(A}}\mid {\rm{B\c{C}C) }}\)

(e):

We are asked to find

\(\begin{aligned}{\rm{P(A}}\mid {\rm{B\c{C}C) = }}\frac{{{\rm{P(A\c{C}B\c{C}C)}}}}{{{\rm{P(B\c{C}C)}}}}\\{\rm{ = }}\frac{{{\rm{0}}{\rm{.54}}}}{{{\rm{0}}{\rm{.68}}}}\\{\rm{ = 0}}{\rm{.7941}}{\rm{.}}\end{aligned}\)

where we used definition of conditional probability:

Conditional probability of A given that the event B has occurred, for which\({\rm{P(B) > 0}}\), is

\({\rm{P(A}}\mid {\rm{B) = }}\frac{{{\rm{P(A\c{C}B)}}}}{{{\rm{P(B)}}}}\)

for any two event \({\rm{A}}\)and\({\rm{B}}\).

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Consider independently rolling two fair dice, one red and the other green. Let A be the event that the red die shows \({\rm{3}}\) dots, B be the event that the green die shows \({\rm{4}}\) dots, and C be the event that the total number of dots showing on the two dice is \({\rm{7}}\). Are these events pairwise independent (i.e., are \({\rm{A}}\) and \({\rm{B}}\) independent events, are \({\rm{A}}\) and \({\rm{C}}\) independent, and are \({\rm{B}}\) and \({\rm{C}}\) independent)? Are the three events mutually independent?

An insurance company offers four different deductible levels—none, low, medium, and high—for its home owner’s policy holders and three different levels—low, medium, and high—for its automobile policyholders. The accompanying table gives proportions for the various categories of policyholders who have both types of insurance. For example, the proportion of individuals with both low homeowner’s deductible and low auto deductible is .06(6% of all such individuals).

±á´Ç³¾±ð´Ç·É²Ô±ð°ù’s

Auto N L M H

L .04 .06 .05 .03

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b. What is the probability that the individual has a low auto deductible? A low homeowner’s deductible?

c. What is the probability that the individual is in the same category for both auto and homeowner’s deductibles?

d. Based on your answer in part (c), what is the probability that the two categories are different?

e. What is the probability that the individual has at least one low deductible level?

f. Using the answer in part (e), what is the probability that neither deductible level is low?

In any Ai independent of any other \({\rm{Aj}}\)? Answer using the multiplication property for independent events.

A certain system can experience three different types of defects. Let \({{\rm{A}}_{\rm{1}}}\)\({\rm{(i = 1,2,3)}}\)denote the event that the system has a defect of type Suppose that

\(\begin{aligned}P\left( {{A_1}} \right) &= .12\;\;\;P\left( {{A_2}} \right) = .07\;\;\;P\left( {{A_3}}\right) = .05 \hfill \\P\left( {{A_1}E {A_2}} \right) = .13\;\;\;P\left( {{A_1}E {A_3}}\right) &= .14 \hfill \\P\left( {{A_2}E {A_2}} \right) = .10\;\;\;P\left( {{A_1}{C}{A_3}{C}{A_7}} \right) &= .01 \hfill \\\end{aligned} \)

a. What is the probability that the system does not have a type 1 defect?

b. What is the probability that the system has both type 1 and type 2 defects?

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