1)
If the top five of the 40 dealerships are
going to be recognized as “superior” performers, how many different ways could
the five be selected?
A.
427,234
B.
5
C.
658,008
D.
78,960,960
2)
48% of the customers buy a Dodge. If three car buyers are randomly selected what
is the probability that they all bought a Dodge?
A.
0.48
B.
0.11
C.
0.52
D.
0.16
Use the following information for questions
13-15. 12 people come into the
dealership every day and 65% of them buy a car.
3)
What is the probability that no more than 6
people will buy a car?
A.
0.50
B.
0.21
C.
0.13
D.
0.65
4)
What is the probability that more than 8
people will buy a car?
A.
0.42
B.
0.65
C.
0.58
D.
0.35
5)
What is the expected number of cars sold?
A.
7.8
B.
6.0
C.
12.0
D.
4.7
Use the following data for problems
16-19.
The average profit for a different set of 40
car dealerships was $45,000 with a standard deviation of $8,500. Assume profit is normally distributed
6)
What is a probability that a randomly selected
car dealership will have sales of exactly $45,000?
A.
0.50
B.
0.00
C.
0.25
D.
0.75
7)
What is a probability that a randomly selected
car dealership will have sales more than $40,000?
A.
0.28
B.
0.36
C.
0.72
D.
0.86
8)
What is the probability that a randomly
selected car dealership will have sales between $25,000 and $55,000?
A.
0.68
B.
0.87
C.
0.23
D.
0.46
For questions 9 and 10 use the following
information. A sample of 75 pizza
deliveries each day were checked for on time delivery at a local pizza
shop. The chart below displays the
number of deliveries from this sample that exceeded the stores stated delivery
time in each sample. Use a 99.7% level
(Z = 3)
|
Day |
Deliveries Late |
|
1 |
2 |
|
2 |
4 |
|
3 |
1 |
|
4 |
3 |
|
5 |
0 |
|
6 |
7 |
|
7 |
9 |
|
8 |
2 |
|
9 |
0 |
|
10 |
4 |
|
11 |
3 |
|
12 |
1 |
9)
What is the upper control limit on this chart?
A.
0.085
B.
8.20
C.
0.04
D.
0.108
10)
What is the lower control limit on this chart.
A.
-0.028
B.
1.27
C.
0, The lower control limit does not exist.
D.
0.023
For questions 11 and 12 use the following
information. A hotel asked guest
checking to fill out a rating card each day for 10 days. The chart below shows the number of cards
each day with
|
Day |
Cards with Negative |
|
1 |
12 |
|
2 |
8 |
|
3 |
9 |
|
4 |
7 |
|
5 |
12 |
|
6 |
17 |
|
7 |
10 |
|
8 |
4 |
|
9 |
12 |
|
10 |
10 |
11)
Calculate the Upper Control Limit.
A.
19.63
B.
13.28
C.
21.73
D.
10.10
12)
Calculate the Lower Control Limit.
A.
0, the limit does not exist.
B.
3.18
C.
1.47
D.
0.57
The data for questions 13 and 14 are on the
embedded data sheet attached to the test.
Post Cereal weighed 12 boxes each hour for 10 hours. The weights of each of these boxes are on the
data sheet. Use this information to
solve questions 23 and 24.
13)
Calculate the upper and lower control limits
for the mean chart.
A.
UCL = 12.093, LCL = 11.907
B.
UCL = 12.046, LCL = 11.966
C.
UCL = 12.156, LCL = 11.856
D.
UCL = 12.291 LCL = 11.709
14)
Calculate the upper and lower control limits
for the range chart.
A.
UCL = 0.309, LCL = 0
B.
UCL = 0.462, LCL = 0.125
C.
UCL = 0.258, LCL = 0.042
D.
UCL = 0.150, LCL = 0
15)
A local soda company was bottling their
product into 12 ounce cans. The Company
has specification limits of 12.0 ounces +/- 0.2 ounces. Checking a sample of 14 cans each hour for 10
hours, they found that the mean of all the samples was 11.98 ounces with a
range of 0.15 ounces. Calculate the
capability index (Cpk).
A.
1.67
B.
1.36
C.
1.51
D.
0.93
16)
Below are the mean and range charts for a
completed analysis. Which of the
statements below is true?
Mean chart
Range chart
A.
The Mean chart is in control so the Range
chart does not matter.
B.
Both the Mean chart and Range chart are in
control
C.
The Range Chart shows an anomaly that may be a
special cause of variation.
D.
The Mean Chart shows an anomaly that may be a
special cause of variation
The following data set shows the number of
attendees at a local swimming pool and the high temperature that day. Use this data to develop a regression that
will predict the number of attendees based on the predicted high temperature.
|
Temperature |
Pool Attendees |
|
72 |
27 |
|
78 |
41 |
|
75 |
37 |
|
81 |
52 |
|
85 |
70 |
|
76 |
45 |
|
93 |
85 |
|
97 |
103 |
|
76 |
49 |
|
89 |
71 |
|
103 |
98 |
|
95 |
87 |
|
93 |
75 |
17)
What is the correlation coefficient for this
model?
A.
0.940
B.
0.970
C.
-0.884
D.
0.180
18)
Which of these statements below is true?
A.
97% of the variance of the temperature is
explained by the number of attendees
B.
94% of the variance of the number of attendees
is explained by the temperature
C.
94% of the variance of both variables is
explained by the regression
D.
Both A and C are true
19)
What is the sum of square errors for the
model?
A.
39.1
B.
6775.5
C.
7205
D.
429.6
20)
What is the dependent variable (temperature or
attendees)?
A.
Temperature is the dependent variable
B.
Attendees is the dependent variable
C.
Both variables are dependent on each other
D.
Neither of the variables are dependent
Use the following excel regression output to
answer questions 21 – 24
21)
What is the coefficient of determination for
the model?
A.
0,148
B.
0.199
C.
0.923
D.
0.852
22)
What is the correlation coefficient of the
model?
A.
0.923
B.
0.852
C.
-0.923
D.
0.148
23)
What is the p value and is it significant at
the alpha .01 level?
A.
.00014, yes
B.
-6.79, yes
C.
46.16, no
D.
.00014, no
24)
What is the standard error of the regression?
A.
-1.358
B.
19.87
C.
1.815
D.
0.923
Use the following information for questions
25-26.
Below is a small local tire repair shop actual
annual sales report.
|
Year |
Tire sales |
|
1 |
300 |
|
2 |
400 |
|
3 |
450 |
|
4 |
525 |
|
5 |
625 |
25)
Using an exponential smoothing with weight of
? = 0.25, determine the forecasted sales for year 6 (assume the forecast for
year one is 300).
A.
455.08
B.
385.72
C.
410.23
D.
510.28
26)
Find a linear regression (a linear trend)
forecast for year 6.
A.
670.03
B.
680.02
C.
692.50
D.
683.20
Use the following information for questions
27-28.
|
Month |
Actual Sales |
Forecasted sales |
|
1 |
50 |
70 |
|
2 |
83 |
93 |
|
3 |
75 |
80 |
|
4 |
65 |
59 |
|
5 |
59 |
63 |
|
6 |
90 |
89 |
27)
Compute the MAD for the above forecasts:
A.
6.98
B.
6.00
C.
5.66
D.
7.66
28)
Compute MAPD for the above forecasts:
A.
0.058
B.
0.032
C.
0.109
D.
0.981
29)
Computer MSE for the above forecasts:
A.
96.03
B.
96.33
C.
90.16
D.
95.03
Use the following information for questions 30.
|
Year (X) |
q1 |
q2 |
q3 |
q4 |
|
1 |
450 |
500 |
565 |
460 |
|
2 |
455 |
525 |
580 |
550 |
30)
Using the method indicated in your book to
compute seasonally adjusted forecast for q3 (quarter 3) of year 3.
A.
630.12
B.
629.26
C.
625.03
D.
620.11
31)
The given trend equation is Y = 1840 + 135 *
year. The seasonal factor for August is 0.15. Forecast sales for August of year
10.
A.
478.5
B.
450.5
C.
490.5
D.
495.3
32)
Which of the following is not a qualitative
forecasting method?
A.
Delphi method
B.
Management judgment
C.
Jury of executive opinion
D.
Exponential smoothing
Using the following data to answer questions 33-35
|
Activity |
Optimistic |
Most likely |
Pessimistic |
|
A |
5 |
8 |
11 |
|
B |
2 |
5 |
7 |
|
C |
10 |
12 |
13 |
|
D |
3 |
8 |
11 |
|
E |
10 |
13 |
15 |
|
F |
5 |
9 |
15 |
|
G |
5 |
7 |
10 |
33)
What is the mean expected completion time for
activity C?
A.
11.83
B.
10.23
C.
12.09
D.
10.56
34)
There are two activities (C and D) in the
critical path, what is the variance of the critical path?
A.
2.333
B.
1.082
C.
2.028
D.
2.456
35)
What is the standard deviation of activity G?
A.
0.833
B.
0.756
C.
0.652
D.
0.231
Use the following table to answer question
36-39.
|
Activity |
Predecessor |
Completion time |
|
A |
5 |
|
|
B |
3 |
|
|
C |
A |
4 |
|
D |
A |
6 |
|
E |
B |
4 |
|
F |
D, E |
5 |
|
G |
C, F |
6 |
36)
What is the project completion time?
A.
22
B.
20
C.
19
D.
17
37)
Which activities are on the critical path?
A.
A, D, F, G
B.
A, D, E, F
C.
C, F, A
D.
D, F, C
38)
What is the latest finish time for activity F?
A.
12
B.
16
C.
10
D.
9
39)
Which activity has the most slack?
A.
C
B.
A
C.
B
D.
D
40)
You have the following results for a given
period:
Expected completion time of the given project = 44
Variance of project completion time = 5.54
What is the probability of completing the project over 40 days?
A.
0.957
B.
0.886
C.
0.896
D.
0.853
