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Question 1
[removed] |
1. |
Seasonal effects |
[removed] |
2. |
noise dampening response |
[removed] |
3. |
impulse response |
[removed] |
4. |
all of the above |
[removed] |
5. |
none of the above |
5 points
Question 2
[removed] |
1. |
A simple exponential smoothing model |
[removed] |
2. |
Impulse response |
[removed] |
3. |
Noise dampening |
[removed] |
4. |
all of the above |
[removed] |
5. |
none of the above |
5 points
Question 3
[removed] |
1. |
alpha |
[removed] |
2. |
E-bar |
[removed] |
3. |
MAD |
[removed] |
4. |
all of the above |
[removed] |
5. |
none of the above |
5 points
Question 4
trend data that fits in a straight line |
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||
|
|||
short range forecast with no trends or seasonal effects |
|
random data with no seasonal effects or trends |
|
random data that illustrates a trend or seasonal pattern |
|
|
|
20 points
Question 5
[removed] |
1. |
an exponential smoothing forecast method should be used |
[removed] |
2. |
the data must be linear |
[removed] |
3. |
The alpha coefficient should be set close to 1 for exponential smoothing |
[removed] |
4. |
The alpha coefficient should be set close to 0 for exponential smoothing |
[removed] |
5. |
None of the above |
5 points
Question 6
[removed] |
1. |
49.25 |
[removed] |
2. |
50.67 |
[removed] |
3. |
53.00 |
[removed] |
4. |
none of the above |
5 points
Question 7
[removed] |
1. |
April |
[removed] |
2. |
June |
[removed] |
3. |
August |
[removed] |
4. |
October |
[removed] |
5. |
None of the above |
5 points
Question 8
[removed] |
1. |
47.9 |
[removed] |
2. |
53.2 |
[removed] |
3. |
40.8 |
[removed] |
4. |
51.6 |
5 points
Question 9
[removed] |
1. |
10% |
[removed] |
2. |
12% |
[removed] |
3. |
14% |
[removed] |
4. |
16% |
[removed] |
5. |
18% |
5 points
Question 10
[removed] |
1. |
marketing |
[removed] |
2. |
demand estimates |
[removed] |
3. |
sales forecast |
[removed] |
4. |
all of the above |
[removed] |
5. |
none of the above |
5 points
Question 11
[removed] |
1. |
is set equal to the actual value in period 1 |
[removed] |
2. |
varies over a time series of data |
[removed] |
3. |
is a value between 0 and 1 |
[removed] |
4. |
all of the above |
[removed] |
5. |
none of the above |
5 points
Question 12
[removed] |
1. |
seasonal |
[removed] |
2. |
cyclical |
[removed] |
3. |
periodical |
[removed] |
4. |
abnormal |
[removed] |
5. |
following a trend |
5 points
Question 13
[removed] |
1. |
divide each actual value by the trend line intercept |
[removed] |
2. |
divide each actual value by its seasonal index factor |
[removed] |
3. |
divide each actual value by total forecast error |
[removed] |
4. |
divide each actual value by the alpha coefficient |
5 points
Question 14
[removed] |
1. |
1160.82 |
[removed] |
2. |
1807.74 |
[removed] |
3. |
2023.38 |
[removed] |
4. |
3641.59 |
5 points
Question 15
[removed] |
1. |
6.2 |
[removed] |
2. |
7.7 |
[removed] |
3. |
8.3 |
[removed] |
4. |
8.8 |
5 points
Question 16
[removed] |
1. |
time series method for detecting seasonality |
[removed] |
2. |
variation of exponential smoothing method |
[removed] |
3. |
multiple regression method |
[removed] |
4. |
qualitative method which solicits from experts |
[removed] |
5. |
qualitative method for researching similar to data |
5 points
Question 17
[removed] |
1. |
0 |
[removed] |
2. |
100 |
[removed] |
3. |
10 |
[removed] |
4. |
none of the above |
5 points
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