# Stats

```CHAPTER FIVE
Discrete Distributions
C
1.
E
Term
B
E
Term
Variables which take on values only at certain points over a given interval are
called
.
A. point variables
B. continuous random variables
C. discrete random variables
D. value variables
2.
A variable that can take on values at any point over a given interval is called
.
A. a point variable
B. a continuous random variable
C. a discrete random variable
D. a value variable
141
142
Test Bank
A
3.
E
Term
D
A. a discrete random variable
B. a continuous random variable
C. the binomial distribution
D. the normal distribution
4.
E
Term
B
5.
The volume of liquid in an unopened 12-ounce bottle of beer is an example of
.
A. a discrete random variable
B. a continuous random variable
C. the binomial distribution
D. the normal distribution
6.
E
Term
A
The amount of time a patient waits in a doctor's office is an example of
.
A. the normal distribution
B. the binomial distribution
C. a discrete random variable
D. a continuous random variable
E
Term
C
The number of automobiles sold by a dealership in a day is an example of
.
The volume of liquid in an unopened 1-gallon can of paint is an example of
.
A. the binomial distribution
B. the normal distribution
C. a continuous random variable
D. a discrete random variable
7.
The number of defective parts in a lot of 25 parts is an example of
E
A. a discrete random variable
Term
B. a continuous random variable
C. the Poisson distribution
D. the normal distribution
.
Chapter 5: Discrete Distributions
B
8.
E
BCalc
D
You are offered an investment opportunity. Its outcomes and probabilities are
presented in the following table.
P(X)
X
-\$1,000
.40
\$0
.20
+\$1,000
.40
The mean of this distribution is
.
A.
B.
C.
D.
9.
-\$400
\$0
\$200
\$400
You are offered an investment opportunity. Its outcomes and probabilities are
presented in the following table.
P(X)
X
-\$1,000
.40
\$0
.20
+\$1,000
.40
The standard deviation of this distribution is
.
M
BCalc
A. -\$400
B. \$663
C. \$800,000
D. \$894
C
You are offered an investment opportunity. Its outcomes and probabilities are
presented in the following table.
P(X)
X
-\$1,000
.40
\$0
.20
+\$1,000
.40
Which of the following statements is true?
10.
E
BApp
A. This distribution is skewed to the right.
B. This is a binomial distribution.
C. This distribution is symmetric.
D. This distribution is skewed to the left.
143
144
Test Bank
C
11.
You are offered an investment opportunity. Its outcomes and probabilities are
presented in the following table.
P(X)
X
-\$1,000
.10
\$0
.20
+\$1,000
.70
The mean of this distribution is
.
E
BCalc
A.
B.
C.
D.
B
You are offered an investment opportunity. Its outcomes and probabilities are
presented in the following table.
P(X)
X
-\$1,000
.10
\$0
.20
+\$1,000
.70
The standard deviation of this distribution is
.
12.
-\$100
\$0
\$600
\$700
M
BCalc
A. -\$400
B. \$663
C. \$800,000
D. \$894
D
You are offered an investment opportunity. Its outcomes and probabilities are
presented in the following table.
P(X)
X
-\$1,000
.10
\$0
.20
+\$1,000
.70
Which of the following statements is true?
13.
E
BApp
A. This distribution is skewed to the right.
B. This is a binomial distribution.
C. This distribution is symmetric.
D. This distribution is skewed to the left.
Chapter 5: Discrete Distributions
C
14.
145
A market research team compiled the following discrete probability distribution.
In this distribution X represents the number of automobiles owned by a family
residing in Starr County.
X
P(X)
0
0.10
1
0.10
2
0.50
3
0.30
The mean (average) value of X is
.
E
BCalc
A.
B.
C.
D.
B
A market research team compiled the following discrete probability distribution.
In this distribution X represents the number of automobiles owned by a family
residing in Starr County.
X
P(X)
0
0.10
1
0.10
2
0.50
3
0.30
The standard deviation of X is
.
15.
M
BCalc
A.
B.
C.
D.
1.0
1.5
2.0
2.5
0.80
0.89
1.00
2.00
146
Test Bank
D
16.
A market research team compiled the following discrete probability distribution.
In this distribution X represents the number of automobiles owned by a family
residing in Starr County.
X
P(X)
0
0.10
1
0.10
2
0.50
3
0.30
Which of the following statements is true?
E
BApp
A. This distribution is skewed to the right.
B. This is a binomial distribution.
C. This is a normal distribution.
D. This distribution is skewed to the left.
A
A market research team compiled the following discrete probability distribution
for families residing in Randolph County. In this distribution X represents the
number of evenings the family dines outside their home during a week.
X
P(X)
0
0.30
1
0.50
2
0.10
3
0.10
The mean (average) value of X is
.
17.
E
BCalc
A.
B.
C.
D.
1.0
1.5
2.0
2.5
Chapter 5: Discrete Distributions
D
18.
147
A market research team compiled the following discrete probability distribution
for families residing in Randolph County. In this distribution X represents the
number of evenings the family dines outside their home during a week.
X
P(X)
0
0.30
1
0.50
2
0.10
3
0.10
The standard deviation of X is
.
M
BCalc
A.
B.
C.
D.
A
A market research team compiled the following discrete probability distribution
for families residing in Randolph County. In this distribution X represents the
number of evenings the family dines outside their home during a week.
X
P(X)
0
0.30
1
0.50
2
0.10
3
0.10
Which of the following statements is true?
19.
E
BApp
1.00
2.00
0.80
0.89
A. This distribution is skewed to the right.
B. This distribution is skewed to the left.
C. This is a binomial distribution.
D. This is a normal distribution.
148
Test Bank
D
20.
The sales manager at Moss Point Metropolitan Motors compiled the following
discrete probability distribution. In this distribution X represents the number of
cars sold per day at her dealership.
X
P(X)
0
0.25
1
0.50
2
0.25
The mean (average) value of X is
.
E
BCalc
A.
B.
C.
D.
A
The sales manager at Moss Point Metropolitan Motors compiled the following
discrete probability distribution. In this distribution X represents the number of
cars sold per day at her dealership.
X
P(X)
0
0.25
1
0.50
2
0.25
The standard deviation of X is
.
21.
0.5
0
1.5
1.0
M
BCalc
A.
B.
C.
D.
C
The sales manager at Moss Point Metropolitan Motors compiled the following
discrete probability distribution. In this distribution X represents the number of
cars sold per day at her dealership.
X
P(X)
0
0.25
1
0.50
2
0.25
Which of the following statements is true?
22.
E
BApp
0.71
0.50
3.0
1.0
A. This distribution is skewed to the right.
B. This distribution is skewed to the left.
C. This distribution is symmetric.
D. This is a normal distribution.
Chapter 5: Discrete Distributions
C
23.
A Bernoulli process has exactly
possible outcomes.
E
Term
A.
B.
C.
D.
D
If X is the number of successes in an independent series of 10 Bernoulli trials,
then X has a
distribution.
24.
8
4
2
1
M
Term
A.
B.
C.
D.
A
If X has a binomial distribution with p &lt; .5, then the distribution of X is
.
25.
hypergeometric
Poisson
normal
binomial
E
Term
A. skewed to the right.
B. skewed to the left.
C. symmetric.
D. a normal distribution.
C
If X has a binomial distribution with p = .5, then the distribution of X is
.
26.
E
Term
A. skewed to the right.
B. skewed to the left.
C. symmetric.
D. a normal distribution.
B
If X has a binomial distribution with p &gt; .5, then the distribution of X is
.
27.
E
Term
A. skewed to the right.
B. skewed to the left.
C. symmetric.
D. a normal distribution.
149
150
Test Bank
A
28.
The following graph is a binomial distribution with n = 6.
This graph reveals that
M
App
D
A. p &gt; 0.5
B. p = 1.0
C. p = 0
D. p &lt; 0.5
29.
The following graph is a binomial distribution with n = 6.
This graph reveals that
M
App
.
A. p &gt; 0.5
B. p = 1.0
C. p = 0
D. p &lt; 0.5
.
Chapter 5: Discrete Distributions
B
30.
The following graph is a binomial distribution with n = 6.
This graph reveals that
M
App
B
151
.
A. p = 0.5
B. p = 1.0
C. p = 0
D. p &lt; 0.5
31.
Binomial probabilities may be calculated in Excel worksheets by using the
function.
M
Term
A.
B.
C.
D.
A
Hypergeometric probabilities may be calculated in Excel worksheets by using the
function.
32.
=binprobabilty()
=binomdist()
=binomprob()
=probbin()
M
Term
A. =hypergeomdist()
B. =hypergprobabilty()
C. =hypergeoprob()
D. =probhyper()
D
Poisson probabilities may be calculated in Excel worksheets by using the
function.
33.
M
Term
A.
B.
C.
D.
=poissondist()
=poissonprobabilty()
=poissonprob()
=poisson()
152
Test Bank
B
34.
E
App
A
A. using the normal distribution
B. using the binomial distribution
C. using the Poisson distribution
D. using the exponential distribution
35.
E
Calc
C
M
Calc
A fair coin is tossed 5 times. What is the probability that exactly 2 heads are
observed?
A.
B.
C.
D.
36.
M
Calc
D
Twenty five items are sampled. Each of these has the same probability of being
defective. The probability that exactly 2 of the 25 are defective could best be
found by
.
A student randomly guesses the answers to a five question true/false test. If there
is a 50% chance of guessing correctly on each question, what is the probability
that the student misses exactly 1 question?
A.
B.
C.
D.
37.
0.313
0.073
0.400
0.156
0.200
0.031
0.156
0.073
A student randomly guesses the answers to a five question true/false test. If there
is a 50% chance of guessing correctly on each question, what is the probability
that the student misses no questions?
A.
B.
C.
D.
0.000
0.200
0.500
0.031
Chapter 5: Discrete Distributions
B
38.
153
Pinky Bauer, Chief Financial Officer of Harrison Haulers, Inc., suspects
irregularities in the payroll system, and orders an inspection of a random sample
of vouchers issued since January 1, 1993. A sample of ten vouchers is randomly
selected, without replacement, from the population of 2,000 vouchers. Each
voucher in the sample is examined for errors; and X is the number of sample
vouchers with errors. If 20% of the population of vouchers contain errors, P(X=0)
is
.
E
BCalc
A.
B.
C.
D.
C
Pinky Bauer, Chief Financial Officer of Harrison Haulers, Inc., suspects
irregularities in the payroll system, and orders an inspection of a random sample
of vouchers issued since January 1, 1993. A sample of ten vouchers is randomly
selected, without replacement, from the population of 2,000 vouchers. Each
voucher in the sample is examined for errors; and X is the number of sample
vouchers with errors. If 20% of the population of vouchers contain errors, P(X&gt;0)
is
.
39.
0.8171
0.1074
0.8926
0.3020
M
BCalc
A.
B.
C.
D.
B
Pinky Bauer, Chief Financial Officer of Harrison Haulers, Inc., suspects
irregularities in the payroll system, and orders an inspection of a random sample
of vouchers issued since January 1, 1993. A sample of ten vouchers is randomly
selected, without replacement, from the population of 2,000 vouchers. Each
voucher in the sample is examined for errors; and X is the number of sample
vouchers with errors. If 20% of the population of vouchers contain errors, the
mean value of X is
.
40.
M
BCalc
0.8171
0.1074
0.8926
0.3020
A. 400
B. 2
C. 200
D. 5
154
Test Bank
A
41.
Pinky Bauer, Chief Financial Officer of Harrison Haulers, Inc., suspects
irregularities in the payroll system, and orders an inspection of a random sample
of vouchers issued since January 1, 1993. A sample of ten vouchers is randomly
selected, without replacement, from the population of 2,000 vouchers. Each
voucher in the sample is examined for errors; and X is the number of sample
vouchers with errors. If 20% of the population of vouchers contain errors, the
standard deviation of X is
.
M
BCalc
A.
B.
C.
D.
C
Dorothy Little purchased a mailing list of 2,000 names and addresses for her mail
order business, but after scanning the list she doubts the authenticity of the list.
She randomly selects five names from the list for validation. If 40% of the names
on the list are not authentic, and X is the number of non-authentic names in her
sample, P(X=0) is
.
42.
1.26
1.60
14.14
3.16
E
BCalc
A.
B.
C.
D.
A
Dorothy Little purchased a mailing list of 2,000 names and addresses for her mail
order business, but after scanning the list she doubts the authenticity of the list.
She randomly selects five names from the list for validation. If 40% of the names
on the list are not authentic, and X is the number of non-authentic names in her
sample, P(X&lt;2) is
.
43.
M
BCalc
A.
B.
C.
D.
0.8154
0.0467
0.0778
0.4000
0.4370
0.9853
0.9785
0.2333
Chapter 5: Discrete Distributions
D
44.
155
Dorothy Little purchased a mailing list of 2,000 names and addresses for her mail
order business, but after scanning the list she doubts the authenticity of the list.
She randomly selects five names from the list for validation. If 40% of the names
on the list are not authentic, and X is the number of non-authentic names in her
sample, P(X&gt;0) is
.
M
BCalc
A.
B.
C.
D.
B
Dorothy Little purchased a mailing list of 2,000 names and addresses for her mail
order business, but after scanning the list she doubts the authenticity of the list.
She randomly selects five names from the list for validation. If 40% of the names
on the list are not authentic, and X is the number on non-authentic names in her
sample, the expected (average) value of X is
.
45.
0.2172
0.9533
0.1846
0.9222
M
BCalc
A.
B.
C.
D.
B
If X is a binomial random variable with n=8 and p=0.6, the mean value of X is
.
46.
M
Calc
D
M
Calc
A.
B.
C.
D.
47.
2.50
2.00
1.50
1.25
6
4.8
3.2
8
If X is a binomial random variable with n=8 and p=0.6, the standard deviation of
X is
.
A.
B.
C.
D.
4.8
3.2
1.92
1.39
156
Test Bank
C
48.
M
Calc
B
A. 6
B. 10
C. 4
D. 2.4
49.
M
Calc
D
50.
M
Calc
If X is a binomial random variable with n=8 and p=0.6, what is the probability
that X is equal to 4?
A.
B.
C.
D.
51.
E
Calc
A
If X is a binomial random variable with n=8 and p=0.2, the variance of X is
.
A. 1.6
B. 1.28
C. 4
D. 0.96
E
Calc
B
If X is a binomial random variable with n=10 and p=0.4, the mean of X is
.
If X is a binomial random with n=8 and p=0.6, what is the probability that X is
equal to 5?
A.
B.
C.
D.
52.
0.500
0.005
0.124
0.232
0.625
0.279
0.209
0.300
If X is a binomial random with n=8 and p=0.6, what is the probability that X is
less than or equal to 2?
A.
B.
C.
D.
0.050
0.009
0.041
0.375
Chapter 5: Discrete Distributions
C
53.
M
Calc
B
M
Calc
A
55.
56.
M
Calc
B
0.167
0.833
0.215
0.800
If X is a binomial random with n=10 and p=0.4, what is the probability that X is
equal to 3?
A. 0.215
B. 0.057
C. 0.300
D. 0.120
If X is a binomial random with n=10 and p=0.4, what is the probability that X is
less than 2?
A.
B.
C.
D.
57.
0.124
0.991
0.950
0.011
If X is a binomial random with n=10 and p=0.4, what is the probability that X is
greater than 2?
A.
B.
C.
D.
E
Calc
B
If X is a binomial random with n=8 and p=0.6, what is the probability that X is
greater than 2?
A.
B.
C.
D.
54.
157
0.167
0.046
0.040
0.006
The Poisson distribution focuses on the number of discrete occurrences
M A. in &quot;n&quot; trials
Term
B. over some interval or continuum
C. in &quot;n&quot; trials where sampling is done without replacement
D. in a Bernoulli trial
.
158
Test Bank
C
58.
The long-run average or mean of a Poisson distribution is usually referred to as
.




M
Term
A.
B.
C.
D.
A
The variance of a Poisson distribution is equal to
59.
.
M
Term
A. 
B. /2
C. 2
D. 
D
If lambda is 3 occurrences per five minute time interval, the probability of getting
5 occurrences over a five minute interval is
.
60.
M
Calc
C
A.
B.
C.
D.
61.
M
Calc
A
M
Calc
62.
0.0940
0.0417
0.1500
0.1008
If lambda () is 3 occurrences per five minute time interval, the probability of
getting 2 occurrences over a five minute interval is
.
A. 0.2700
B. 0.0498
C. 0.2240
D. 0.0001
If lambda () is 4 occurrences per five minute time interval, the probability of
getting 3 occurrences over a five minute interval is
.
A.
B.
C.
D.
0.1954
0.0183
0.2237
0.1680
Chapter 5: Discrete Distributions
C
63.
M
Calc
C
M
Calc
D
65.
M
BCalc
5
60
30
10
If lambda () is 3 occurrences per five minute time interval, then if we wished to
analyze the number of occurrences per hour, we would use an adjusted lambda of
.
A.
B.
C.
D.
66.
0.1093
0.0067
0.1755
0.8000
If lambda () is 5 occurrences per ten minute time interval, then if we wished to
analyze the number of occurrences per hour, we would use an adjusted lambda of
.
A.
B.
C.
D.
M
Calc
D
If lambda () is 5 occurrences per ten minute time interval, the probability of
getting 4 occurrences over a ten minute interval is
.
A.
B.
C.
D.
64.
159
60
12
20
36
On Saturdays, cars arrive at Sami Schmitt's Scrub and Shine Car Wash at the rate
of 6 cars per fifteen minute interval. Using the Poisson distribution, the
probability that five cars will arrive during the next fifteen minute interval is
.
A.
B.
C.
D.
0.1008
0.0361
0.1339
0.1606
160
Test Bank
B
67.
H
BCalc
B
68.
On Saturdays, cars arrive at Sami Schmitt's Scrub and Shine Car Wash at the rate
of 6 cars per fifteen minute interval. Using the Poisson distribution, the
probability that five cars will arrive during the next five minute interval is
.
A. 0.1008
B. 0.0361
C. 0.1339
D. 0.1606
The hypergeometric distribution is similar to the binomial distribution except that
.
E
Term
A. sampling is done with replacement in the hypergeometric
B. sampling is done without replacement in the hypergeometric
C. X does not represent the number of successes in the hypergeometric
D. there are more than two possible outcomes in the hypergeometric
A
Suppose a committee of 3 people is to be selected from a group consisting of 4
men and 5 women. What is the probability that all three people selected are men?
69.
M
Calc
D
A.
B.
C.
D.
70.
M
Calc
C
Suppose a committee of 3 people is to be selected from a group consisting of 4
men and 5 women. What is the probability that one man and two women are
selected?
A.
B.
C.
D.
71.
M
BCalc
0.05
0.33
0.11
0.80
0.15
0.06
0.33
0.48
Aluminum castings are processed in lots of five each. A sample of two castings is
randomly selected from each lot for inspection. A particular lot contains one
defective casting; and X is the number of defective castings in the sample.
P(X=0) is
.
A.
B.
C.
D.
0.2
0.4
0.6
0.8
Chapter 5: Discrete Distributions
161
162
Test Bank
B
72.
Aluminum castings are processed in lots of five each. A sample of two castings is
randomly selected from each lot for inspection. A particular lot contains one
defective casting; and X is the number of defective castings in the sample.
P(X=1) is
.
M
BCalc
A.
B.
C.
D.
A
Circuit boards for wireless telephones are etched, in an acid bath, in batches of
100 boards. A sample of seven boards is randomly selected from each lot for
inspection. A particular batch contains two defective boards; and X is the number
of defective boards in the sample. P(X=1) is
.
73.
0.2
0.4
0.6
0.8
M
BCalc
A.
B.
C.
D.
C
Circuit boards for wireless telephones are etched, in an acid bath, in batches of
100 boards. A sample of seven boards is randomly selected from each lot for
inspection. A particular batch contains two defective boards; and X is the number
of defective boards in the sample. P(X=2) is
.
74.
0.1315
0.8642
0.0042
0.6134
M
BCalc
A.
B.
C.
D.
B
Circuit boards for wireless telephones are etched, in an acid bath, in batches of
100 boards. A sample of seven boards is randomly selected from each lot for
inspection. A particular batch contains two defective boards; and X is the number
of defective boards in the sample. P(X=0) is
.
75.
M
BCalc
A.
B.
C.
D.
0.1315
0.8642
0.0042
0.6134
0.1315
0.8642
0.0042
0.6134
Chapter 5: Discrete Distributions
D
76.
163
Ten policyholders file claims with CareFree Insurance. Three of these claims are
fraudulent. Claims manager Earl Evans randomly selects three of the ten claims
for thorough investigation. If X represents the number of fraudulent claims in
Earl's sample, P(X=0) is
.
M
BCalc
A.
B.
C.
D.
A
Ten policyholders file claims with CareFree Insurance. Three of these claims are
fraudulent. Claims manager Earl Evans randomly selects three of the ten claims
for thorough investigation. If X represents the number of fraudulent claims in
Earl's sample, P(X=1) is
.
77.
0.0083
0.3430
0.0000
0.2917
M
BCalc
A.
B.
C.
D.
B
If sampling is performed without replacement, the hypergeometric distribution
should be used. However, the binomial may be used to approximate this if
.
78.
0.5250
0.4410
0.3000
0.6957
E
Term
A.
B.
C.
D.
D
One hundred policyholders file claims with CareFree Insurance. Ten of these
claims are fraudulent. Claims manager Earl Evans randomly selects four of the
ten claims for thorough investigation. If X represents the number of fraudulent
claims in Earl's sample, X has a
distribution.
79.
M
BApp
A.
B.
C.
D.
n &gt; 5%N
n &lt; 5%N
the population size is very small
there are more than two possible outcomes of each trial
continuous
normal
binomial
hypergeometric
164
Test Bank
B
80.
One hundred policyholders file claims with CareFree Insurance. Ten of these
claims are fraudulent. Claims manager Earl Evans randomly selects four of the
ten claims for thorough investigation. If X represents the number of fraudulent
claims in Earl's sample, X has a
.
H
BApp
A. normal distribution
B. hypergeometric distribution, but may be approximated by a binomial
C. binomial distribution, but may be approximated by a normal
D. binomial distribution, but may be approximated by a Poisson
A
Using the Poisson tables, find P(X=2) if  =2.3.
81.
E
Calc
D
A.
B.
C.
D.
82.
E
Calc
B
Using the Poisson tables, find P(X=5) if  =2.6.
A.
B.
C.
D.
83.
0.2652
0.2700
0.2306
0.2033
0.0804
0.0417
0.1414
0.0735
Using the Poisson tables, find P(X=5) if  =3.6.
E A. 0.1322
Calc
B. 0.1377
C. 0.1912
D. 0.1075
C
84.
Using the Poisson tables, find P(X=6) if  = 5.6.
E A. 0.1697
Calc
B. 0.1490
C. 0.1584
D. 0.1267
Chapter 5: Discrete Distributions
A
85.
E
Calc
A
A.
B.
C.
D.
86.
E
Calc
C
87.
E
Calc
A
E
Calc
C
E
Calc
3.6
0.7
0.3
8.4
In a binomial distribution, n=10 and p=0.6. What is &quot;q&quot;?
A.
B.
C.
D.
90.
0.001
0.000
0.003
0.014
In a binomial distribution, n=12 and p=0.3. What is &quot;q&quot;?
A.
B.
C.
D.
89.
0.171
0.080
0.111
0.024
Using the binomial tables, if n=15 and p=.8 find P(X=7).
A.
B.
C.
D.
88.
0.166
0.180
0.002
0.074
Using the binomial tables, if n=25 and p=.3 find P(X=7).
A.
B.
C.
D.
E
Calc
B
Using the binomial tables, if n=20 and p=.4 find P(X=7).
0.4
0.7
6
4
In a binomial distribution, n=10 and p=0.6. What is the mean?
A.
B.
C.
D.
2.4
4
6
5
165
166
Test Bank
A
91.
M
Calc
B
A.
B.
C.
D.
92.
E
Calc
D
2.4
4
6
0.24
The Poisson distribution is being used to approximate a binomial distribution. If
n=40 and p=0.06, what value of lambda would be used?
A. 0.06
B. 2.4
C. 0.24
D. 24
93.
E
Calc
C
In a binomial distribution, n=10 and p=0.6. What is the variance?
The Poisson distribution is being used to approximate a binomial distribution. If
n=60 and p=0.02, what value of lambda would be used?
A.
B.
C.
D.
94.
0.02
12
0.12
1.2
The number of phone calls arriving at a switchboard in a 10 minute time period
would best be modeled with the
.
M
BApp
A. binomial distribution
B. hypergeometric distribution
C. Poisson distribution
D. hyperbinomial distribution
A
The number of defects per 1,000 feet of extruded plastic pipe is best modeled with
the
.
95.
M
BApp
A. Poisson distribution
B. Pascal distribution
C. binomial distribution
D. hypergeometric distribution
Chapter 5: Discrete Distributions
B
96.
The number of defects per square inch of hard disk surface is best modeled with
the
.
M
BApp
A. negative binomial distribution
B. Poisson distribution
C. binomial distribution
D. hypergeometric distribution
B
The probability of selecting 2 male employees and 3 female employees for
promotions in a small company would best be modeled with the
.
97.
167
M
BApp
A. binomial distribution
B. hypergeometric distribution
C. Poisson distribution
D. hyperbinomial distribution
B
The probability of selecting 3 defective items and 7 good items from a warehouse
containing 10 defective and 50 good items would best be modeled with the
.
98.
M
BApp
A. binomial distribution
B. hypergeometric distribution
C. Poisson distribution
D. hyperbinomial distribution
A
The probability of a student randomly guessing the answers to 25 multiple choice
questions is best modeled with the
.
99.
M
App
A 100.
M
BApp
A. binomial distribution
B. hypergeometric distribution
C. Poisson distribution
D. hyperbinomial distribution
The probability of getting 3 defective items and 7 good items in a group of 10
items as they come off an assembly line that is known to produce 3% defective is
best modeled with the
.
A. binomial distribution
B. hypergeometric distribution
C. Poisson distribution
D. hyperbinomial distribution
168
Test Bank
C 101.
The number of people arriving at a bank in a 15 minute time interval is best
modeled using the
.
M
BApp
A. binomial distribution
B. hypergeometric distribution
C. Poisson distribution
D. hyperbinomial distribution
Chapter 5: Discrete Distributions
102.
169
Alissa Roots has inherited \$50,000 from her grandmother, and is evaluating
investment alternatives. One alternative, insured 12-month certificates of deposit,
offers 3% interest with no risk . Her other alternatives, a growth stock and a
mutual fund, are risky. Their rates of return fluctuate from year to year; there are
no guarantees. Historical performances of these alternatives are presented in the
following probability distributions of annual rates of return.
Growth Stock
Mutual Fund
Return
P(Return)
Return P(Return)
-10%
0.1
-5%
0.1
0%
0.4
0%
0.3
40%
0.5
15%
0.6
Alissa has no immediate need for cash, but will need \$10,000 in one year for a
down payment on a house. The remainder is available for long-term investments.
Evaluate Alissa's investment alternatives. Explain the relevance of the mean and
the variance of these distributions to Alissa. What advice would you give her?
How (in what amounts or proportions) should she allocate her inheritance among
the alternatives?
M
BApp
170
Test Bank
103.
Duane Morgan, a market researcher at Kitchen Ease, Inc., is assessing alternative
promotional strategies for a new kitchen wrap product. He is concentrating on
two attributes of the product: (1) its low cost, and (2) its superior biodegradable
characteristics. In test market X, his promotional materials emphasized low cost,
and he emphasized the biodegradable properties in test market Y. During the test,
Duane carefully monitored repeat purchases by households in each test market.
His findings are summarized in the following probability distributions, where X is
the percent of households in the 'low cost' test market making repeat purchases,
and Y is the percent of households in the 'biodegradable' test market making
repeat purchases.
X
0
5
10
15
20
25
P(X)
.55
.25
.10
.05
.03
.02
Y
0
5
10
15
20
25
P(Y)
.05
.10
.35
.35
.10
.05
Discuss the managerial and ethical considerations of this situation. What can
Duane conclude from these data? What other factors may help explain the
differences between the two distributions? What graphic depiction should he
choose for his presentation to the product managers?
M
BApp
Chapter 5: Discrete Distributions
104.
171
Troy Hodges is preparing the revise the operational plans and procedures for the
regional port. Accordingly, he has collected data on the number of high-tonnage,
dry cargo ships arriving per day for a period of forty days. (One hundred three
ships arrived during the period.) Analysis of these data will support formulation
of staffing plans for crews to unload and service the vessels.
Day Arrivals
1
2
2
3
3
4
4
0
5
4
6
1
7
0
8
1
9
1
10
3
Day Arrivals
11
1
12
5
13
6
14
2
15
1
16
0
17
1
18
0
19
2
20
2
Day Arrivals
21
2
22
5
23
2
24
6
25
7
26
5
27
3
28
6
29
2
30
2
Day Arrivals
31
2
32
2
33
2
34
4
35
1
36
0
37
4
38
2
39
3
40
4
Assume that the number of arrivals per day has a Poisson distribution.
a. What is the value of  for the arrival distribution?
b. What is the probability of zero arrivals in any given day?
c. Troy's standard plan should provide a 90% service rate -- it should include
adequate manpower and other resources to service 90% of the vessels on their
arrival date. How many arrivals per day should Troy's standard plan
anticipate?
M
BApp
172
Test Bank
105.
Consider the following graphs of two Poisson distributions. One has  = 4, and
the other has  = 7.
0.20
P(X)
0.15
0.10
0.05
0.00
0
2
4
6
8
10
12
14
X
0.20
P(X)
0.15
0.10
0.05
0.00
0 1 2 3 4 5 6 7 8 9 10 11
X
Describe the distributions and explain why the graphs take the shape that they do.
M
BApp
Chapter 5: Discrete Distributions
173
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