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The table below features three forecasting models used on the same set of data.In a forecasting application for 20 time periods, there are 10 negative errors and 10 positive errors.This indicates the model is performing well.(2)Refer to the following graph:In #3, which method (if any) is most appropriate?(4)In a given application, we are using regression with seasonal indices.The regression model is y = 42 + 2.5t.The seasonal indices for quarters 1-4 are 0.85, 0.92, 0.98, and 1.25, respectively.The predicted value for period 20 is ___________.(5) If our data contains seasonality but no trend, exponential smoothing is appropriate.(2)Annual data can exhibit seasonality.(2)We can assess quarterly seasonality with one year of data.(2) Model 1 Model 2 Model 3 Type Exponential Smoothing Regression Seasonal & Trend MSE 8755.3 4876.2 5945.8 Based solely on the information in this output, which of the following is the best answer?(5) The data set contains no trend or seasonality. The data set contains trend but no seasonality. The data set contains seasonality but no trend. The data set probably contains cyclicality. The data set contains both trend and seasonality. a.True b.False Which of the following apply?(8) The data contain a trend component.The data contain an irregular (random) component. b.The data contain a seasonal component. c.The data ,contain a cyclical component. a.Exponential smoothing. b.Regression. c.Regression with seasonal indices. d.None of the above. 5.In #3, which of the following is most appropriate regarding sales?(4) a.We should use all of the data in our model. b.We should use only periods 5-16 in our model. c.We should use only periods 9-16 in our model. d.We should use only periods 13-16 in our model. e.We should use only periods 1-12 in our model. 6.Refer to the Excel output on the final pages.Here, we are tracking the number of orders placed by week for a 20-week period.The first set of output is for an exponential smoothing model with α = 0.25.The second set of output is for a regression.Which of the following is most appropriate?(3) a.The exponential smoothing model is most appropriate. b.The regression is most appropriate. c.Another model would be more appropriate. 7.The model with the lower MSE is always the most appropriate model.(2) a.True b.False TrueFalse TrueFalse TrueFalse
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QM 662 Exam II
1. The table below features three forecasting models used on the same set of data.
Model 1
Model 2
Model 3
Type
Exponential
Smoothing
Regression
Seasonal & Trend
MSE
8755.3
4876.2
5945.8
Based solely on the information in this output, which of the following is the best answer? (5)
a.
b.
c.
d.
e.
The data set contains no trend or seasonality.
The data set contains trend but no seasonality.
The data set contains seasonality but no trend.
The data set probably contains cyclicality.
The data set contains both trend and seasonality.
2. In a forecasting application for 20 time periods, there are 10 negative errors and 10
positive errors. This indicates the model is performing well. (2)
a. True
b. False
3. Refer to the following graph:
Quarterly Sales (in \$)
70000
60000
50000
40000
30000
20000
10000
0
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
Which of the following apply? (8)
a.
b.
c.
d.
The data contain a trend component.
The data contain a seasonal component.
The data ,contain a cyclical component.
The data contain an irregular (random) component.
4. In #3, which method (if any) is most appropriate? (4)
a.
b.
c.
d.
Exponential smoothing.
Regression.
Regression with seasonal indices.
None of the above.
5. In #3, which of the following is most appropriate regarding sales? (4)
a.
b.
c.
d.
e.
We should use all of the data in our model.
We should use only periods 5-16 in our model.
We should use only periods 9-16 in our model.
We should use only periods 13-16 in our model.
We should use only periods 1-12 in our model.
6. Refer to the Excel output on the final pages. Here, we are tracking the number of orders
placed by week for a 20-week period. The first set of output is for an exponential
smoothing model with α = 0.25. The second set of output is for a regression. Which of
the following is most appropriate? (3)
a. The exponential smoothing model is most appropriate.
b. The regression is most appropriate.
c. Another model would be more appropriate.
7. The model with the lower MSE is always the most appropriate model. (2)
a. True
b. False
8. In a given application, we are using regression with seasonal indices. The regression
model is y = 42 + 2.5t. The seasonal indices for quarters 1-4 are 0.85, 0.92, 0.98, and
1.25, respectively. The predicted value for period 20 is ___________. (5)
9. If our data contains seasonality but no trend, exponential smoothing is appropriate. (2)
a. True
b. False
10. Annual data can exhibit seasonality. (2)
a. True
b. False
11. We can assess quarterly seasonality with one year of data. (2)
a. True
b. False
Week
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
Orders
45
56
65
63
54
60
54
60
56
57
50
61
47
56
55
Forecast
#N/A
45
47.75
52.0625
54.79688
54.59766
55.94824
55.46118
56.59589
56.44691
56.58519
54.93889
56.45417
54.09063
54.56797
Error
#N/A
11
17.25
10.9375
-0.79688
5.402344
-1.94824
4.538818
-0.59589
0.553085
-6.58519
6.06111
-9.45417
1.909375
0.432031
Error^2
121
297.5625
119.6289
0.63501
29.18532
3.795648
20.60087
0.35508
0.305903
43.36467
36.73706
89.38128
3.645712
0.186651
16
17
18
19
20
52
57
58
61
47
54.67598
54.00698
54.75524
55.56643
56.92482
-2.67598
2.993017
3.244763
5.433572
-9.92482
7.160852
8.958153
10.52849
29.52371
98.50207
MSE =
48.47673
SUMMARY OUTPUT
Regression Statistics
Multiple R
R Square
Standard Error
Observations
0.139263
0.019394
-0.03508
5.524367
20
ANOVA
df
1
18
19
SS
10.86466
549.3353
560.2
Coefficients
57.04211
-0.12782
Standard
Error
2.566242
0.214226
Regression
Residual
Total
Intercept
Week
MS
10.86466
30.51863
F
0.356001
t Stat
22.22787
-0.59666
P-value
1.54E-14
0.558166
Exponential Smoothing
70
60
Orders
50
40
30
Actual
20
Forecast
10
0
1
3
5
7
9
11 13 15 17 19
Week
Significance F
0.558166112