Section (2)
Forecasting
True/false and MCQ questions:
1- The sales force composite forecasting method relies on salespersons’
estimates of expected sales. ( )
2- A time-series model uses a series of past data points to make the forecast.
3- The quarterly "make meeting" of Lexus dealers is an example of a sales
force composite forecast. ( )
4- A naive forecast for September sales of a product would be equal to the
sales in August. ( )
5- One advantage of exponential smoothing is the limited amount of record
keeping involved. ( )
6- Mean Squared Error and Coefficient of Correlation are two measures of
the overall error of a forecasting model. ( )
7- Forecasts are usually classified by time horizon into three categories
a. short-range, medium-range, and long-range
b. finance/accounting, marketing, and operations
c. strategic, tactical, and operational
d. exponential smoothing, regression, and time series
e. departmental, organizational, and industrial
8- A forecast with a time horizon of about 3 months to 3 years is typically
called a
a. long-range forecast
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b. medium-range forecast
c. short-range forecast
d. weather forecast
e. strategic forecast
9- Forecasts used for new product planning, capital expenditures, facility
location or expansion, and R&D typically utilize a
a. short-range time horizon
b. medium-range time horizon
c. long-range time horizon
d. naive method, because there is no data history
e. all of the above
10-The three major types of forecasts used by business organizations are
a. strategic, tactical, and operational
b. economic, technological, and demand
c. exponential smoothing, Delphi, and regression
d. causal, time-series, and seasonal
e. departmental, organizational, and territorial
11- The two general approaches to forecasting are
a. qualitative and quantitative
b. mathematical and statistical
c. judgmental and qualitative
d. historical and associative
e. judgmental and associative
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12- The forecasting model that pools the opinions of a group of experts or
managers is known as the
a. sales force composition model
b. multiple regression
c. jury of executive opinion model
d. consumer market survey model
e. management coefficients model
13- Which of the following is not a type of qualitative forecasting?
a. executive opinions
b. sales force composites
c. consumer surveys
d. the Delphi method
e. moving average
14- Which of the following techniques uses variables such as price and
promotional expenditures, which are related to product demand, to predict
demand?
a. associative models
b. exponential smoothing
c. weighted moving average
d. simple moving average
e. time series
15- Given an actual demand of 103, a previous forecast value of 99, and an
alpha of .4, the exponential smoothing forecast for the next period would be
a. 94.6
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b. 97.4
c. 100.6
d. 101.6
e. 103.0
16- A forecasting method has produced the following over the past five
months. What is the mean absolute deviation?
Actual Forecast Error |Error|
10 11 -1 1
8 10 -2 2
10 8 2 2
6 6 0 0
9 8 1 1
a. -0.2
b. -1.0
c. 0.0
d. 1.2
e. 8.6
17- Given forecast errors of -1, 4, 8, and -3, what is the mean absolute
deviation?
a. 2 b. 3
c. 4 d. 8
e. 16
18- The last four months of sales were 8, 10, 15, and 9 units. The last four
forecasts were 5, 6, 11, and 12 units. The Mean Absolute Deviation (MAD)
is
a. 2 b. -10
c. 3.5 d. 9 e. 10.5
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Problems:
1- Weekly sales of ten-grain bread at the local organic food market are in the
table below. Based on this data, forecast week 9 using a five-week moving
average.
week sales
1 415
2 389
3 420
4 382
5 410
6 432
7 405
8 421
2- Given the following data, calculate the three-year moving averages for
years 4 through 10.
year demand
1 74
2 90
3 59
4 91
5 140
6 98
7 110
8 123
9 99
3- What is the forecast for May based on a weighted moving average applied
to the following past demand data and using the weights: 4, 3, 2 (largest
weight is for most recent data)?
Nov. Dec. Jan. Feb. Mar. April
37 36 40 42 47 43
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4- The last four weekly values of sales were 80, 100, 105, and 90 units. The
last four forecasts (for the same four weeks) were 60, 80, 95, and 75 units.
Calculate MAD, MSE, and MAPE for these four weeks.
5- Use exponential smoothing with α = 0.2 to calculate smoothed averages
and a forecast for period 7 from the data below. Assume the forecast for the
initial period is 7.
Period Demand
1 10
2 8
3 7
4 10
5 12
6 9
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