Exercise on Chapter 5 Forecasting
BSNS2120, J. Wang
Name ___________________________
1. Forecasting is a scientific methodology for predicting the future.
a. True
b. False
2. MAD stands for ____________.
a. moving average decision.
b. median of absolute deviation.
c. mean absolute deviation.
3. MAD means _____________________.
a. the average of absolute forecast errors
b. the total of absolute forecast errors
c. the average of forecast errors
d. the total of forecast errors
4. Suppose July’s forecast was $500 and July’s actual sales was $400. What is the forecast error of
July?
a. $100
b. -$100
c. $500
d. $400
5. Suppose July’s forecast was $500 and July’s actual sales was $400. What is the absolute
forecast error of July?
a. $100
b. -$100
c. $500
d. $400
6. Forecast error of March is the difference between ______________.
a. the actual sales of March and forecast of March
b. the forecast of February and the forecast of March
c. the forecast of March and MAD
7. The __________ MAD the better.
a. smaller
b. larger
8. In 4-period-moving average, the forecast of the current period is the average of the sales of
____________________.
a. any four past periods
b. four most recent past periods
c. four earliest past periods
9. The formula for exponential smoothing is Ft=Ft-1+(At-1-Ft-1), in which  _________
a. is between 0 and 1
b. is between -1 and 1
c. can be any positive number
10. When using the weighted moving average method, if we think the most recent past period’s
sales is most relevant for the forecast of the current period, then we should give the most recent
past period a _______ weight.
a. smaller
b. larger
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11. When using the n-period-moving average method, if we do not want our forecasting responsive
to the random variations or noises in the data, we should select a _________ n.
a. smaller
b. larger
12. When using the exponential smoothing method, if we do not want our forecasting responsive to
the random variations or noises in the data, then we should select a _________ .
a. smaller
b. larger
13. When using the n-period-moving average method, if we want our forecasting more responsive
to the trend in the data, we should select a _________ n.
a. smaller
b. larger
14. When using the exponential smoothing method, if we want our forecasting more responsive to
the trend in the data, we should select a _________ .
a. smaller
b. larger
15 Suppose we have the sales data of last 48 months, and we use the 2-month moving average
method. To calculate the forecast of the current month, we only need the sales data of last two
months.
a. True
b. False
16 Suppose we have the sales data of last 48 months, and we use the exponential smoothing
method with =0.3 and the initial month’s forecast was 580. To calculate the forecast of the
current month, we need to calculate the forecast of each of the past 48 months.
a. True
b. False
17. In a real world application of exponential smoothing, how is the value of  determined?
a. It is determined arbitrarily.
b. It is given by your boss who has obligation to provide that value.
c. You do experiments on various values of  and pick the  that generates smallest MAD.
For questions 18 – 19:
Suppose we have sales data for Jan., Feb., and March as follows:
Jan
$1,500
Feb
$1,000
March
$800
18. What is the forecast of April by using 3-month-moving average?
19. What is the forecast of April by using 2-month-weighted-moving-average with weights (3 for
most recent past period, 2 for second most recent past period)?
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20. ‘Seasonal variations’ refer to _____________.
a. random variations without explainable reasons
b. recurring variations at certain seasons of a year
c. changes due to temperatures
21. When ‘seasonal variations’ are considered, the seasons must always go with the four natural
seasons.
a. True
b. False
22. All seasons must be same in terms of number of periods contained.
a. True
b. False
23. A dummy variable in the regression method for seasonal variations can only take value of 0 or
1.
a. True
b. False
24. If there are two seasons, high and low, for a product, then _____ dummy variable(s) will be
used in the regression model.
a. 0
b. 1
c. 2
d. 3
25. If there are two seasons, high and low, for a product, then _____ independent variables will be
used in the regression model.
a. 0
b. 1
c. 2
d. 3
26. Suppose there are two business seasons in a year, low season and high season. Let Y=sales of
product A; X1=period number (1, 2, 3, …, 24); X2=1 if the period is in the low season, X2=0 if the
period is in the high season. The regression equation derived from the past 24 periods’ data is as
follows:
Y = 3,170 + 18X1 – 350X2.
(a) Calculate the forecast of the sales for the next period which is in the low season.
(b) Calculate the forecast of the sales for the period two periods from now in future which is in the
high season.
Answer: 1.a 2.c 3.a 4.b 5.a 6.a 7.a 8.b 9.a 10.b 11.b 12.a 13.a 14.b 15.a 16.a 17.c 18. 1100 19. 880
20. b 21.b 22.b 23.a 24.b 25.c 26.(a)Y=3170+18*25-350*1=3270 26.(b)3170+18*26-350*0=3638
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