1. Regression analysis was applied between sales in ($1000) and advertising(in $100), and the following regression function was obtained: Y = 61 +4.1X Based on this regression line, if advertising is $10,000, the point estimate for sales (in dollars) is what 2. How do we use a least squares regression line? 3. What is the range for the coefficient of determination? Solution 1) $10000 in advertisement = 100 units so answer = 61 + 4.1 *100 = 4116 units of sales 2) We can use a least square regression line to basically model a set of data. 3) 0<= Co- efficient of determination<=1.

1. 1. Regression is always a superior forecasting method to exponential smoothing, so regression
should be used whenever the appropriate software is available. (Points : 1)
True
False
2. Time-series models rely on judgment in an attempt to incorporate qualitative or subjective
factors into the forecasting model. (Points : 1)
True
False
3. A trend-projection forecasting method is a causal forecasting method. (Points : 1)
True
False
4. Qualitative models attempt to incorporate judgmental or subjective factors into the forecasting
model. (Points : 1)
True
False
5. The naive forecast for the next period is the actual value observed in the current period.
(Points : 1)
True
False
6. Time-series models enable the forecaster to include specific representations of various
qualitative and quantitative factors. (Points : 1)
True
False

2. 7. The fewer the periods over which one takes a moving average, the more accurately the
resulting forecast mirrors the actual data of the most recent time periods. (Points : 1)
True
False
8. A scatter diagram for a time series may be plotted on a two-dimensional graph with the
horizontal axis representing the variable to be forecast (such as sales). (Points : 1)
True
False
9. An advantage of exponential smoothing over a simple moving average is that exponential
smoothing requires one to retain less data. (Points : 1)
True
False
10. A seasonal index of 1 means that the season is average. (Points : 1)
True
False
11. When the smoothing constant a = 1, the exponential smoothing model is equivalent to the
nave forecasting model. (Points : 1)
True
False
12. In a second order exponential smoothing, a low _ gives less weight to more recent trends
(Points : 1)
True
False
13. A seasonal index must be between -1 and +1. (Points : 1)

3. True
False
14. The process of isolating linear trend and seasonal factors to develop a more accurate forecast
is called regression. (Points : 1)
True
False
15. Adaptive smoothing is analogous to exponential smoothing where the coefficients and are
periodically updated to improve the forecast. (Points : 1)
True
False
16. A graphical plot with sales on the Y axis and time on the X axis is a (Points : 1)
sscatter diagram.
trend projection.
bar chart.
line graph.
radar chart.
17. A medium-term forecast is considered to cover what length of time? (Points : 1)
2-4 weeks
2-4 years
5-10 years
20 years
1 month to 1 year
18. Assume that you have tried three different forecasting models. For the first, the MAD = 2.5,
for the second, the MSE = 10.5, and for the third, the MAPE = 2.7. We can then say: (Points : 1)
the third method is the best.
methods one and three are preferable to method two.

4. the second method is the best.
method two is least preferred.
none of the above
19. Which of the following methods produces a particularly stiff penalty in periods with large
forecast errors? (Points : 1)
MAPE
Decomposition
MAD
MSE
Bias
20. Enrollment in a particular class for the last four semesters has been 122, 128, 100, and 155
(listed from oldest to most recent). The best forecast of enrollment next semester, based on a
three-semester moving average, would be (Points : 1)
127.7
126.3
168.3
116.7
135.0
Solution
1. Regression is always a superior forecasting method to exponential smoothing, so regression
should be used whenever the appropriate software is available. (Points : 1)
True
False
2. Time-series models rely on judgment in an attempt to incorporate qualitative or subjective
factors into the forecasting model. (Points : 1)
True

5. False
3. A trend-projection forecasting method is a causal forecasting method. (Points : 1)
True
False
4. Qualitative models attempt to incorporate judgmental or subjective factors into the forecasting
model. (Points : 1)
True
False
5. The naive forecast for the next period is the actual value observed in the current period.
(Points : 1)
True
False
6. Time-series models enable the forecaster to include specific representations of various
qualitative and quantitative factors. (Points : 1)
True
False
7. The fewer the periods over which one takes a moving average, the more accurately the
resulting forecast mirrors the actual data of the most recent time periods. (Points : 1)
True
False
8. A scatter diagram for a time series may be plotted on a two-dimensional graph with the
horizontal axis representing the variable to be forecast (such as sales). (Points : 1)
True
False

6. 9. An advantage of exponential smoothing over a simple moving average is that exponential
smoothing requires one to retain less data. (Points : 1)
True
False
10. A seasonal index of 1 means that the season is average. (Points : 1)
True
False
11. When the smoothing constant a = 1, the exponential smoothing model is equivalent to the
nave forecasting model. (Points : 1)
True
False
12. In a second order exponential smoothing, a low _ gives less weight to more recent trends
(Points : 1)
True
False
13. A seasonal index must be between -1 and +1. (Points : 1)
True
False
14. The process of isolating linear trend and seasonal factors to develop a more accurate forecast
is called regression. (Points : 1)
True
False

7. 15. Adaptive smoothing is analogous to exponential smoothing where the coefficients and are
periodically updated to improve the forecast. (Points : 1)
True
False
16. A graphical plot with sales on the Y axis and time on the X axis is a (Points : 1)
sscatter diagram.
trend projection.
bar chart.
line graph.
radar chart.
17. A medium-term forecast is considered to cover what length of time? (Points : 1)
2-4 weeks
2-4 years
5-10 years
20 years
1 month to 1 year
18. Assume that you have tried three different forecasting models. For the first, the MAD = 2.5,
for the second, the MSE = 10.5, and for the third, the MAPE = 2.7. We can then say: (Points : 1)
the third method is the best.
methods one and three are preferable to method two.
the second method is the best.
method two is least preferred.
none of the above
19. Which of the following methods produces a particularly stiff penalty in periods with large
forecast errors? (Points : 1)
MAPE
Decomposition
MAD

8. MSE
Bias
20. Enrollment in a particular class for the last four semesters has been 122, 128, 100, and 155
(listed from oldest to most recent). The best forecast of enrollment next semester, based on a
three-semester moving average, would be (Points : 1)
127.7
126.3
168.3
116.7
135.0