Name:
Class:
Date:
chapter 9
Indicate whether the statement is true or false.
1. In the context of causal forecasting models with multiple regression, an R-squared (R2) value of 0.70 means that 30
percent of the variation in the dependent variable is explained by the independent variable.
a. True
b. False
2. Forecasting is a key component in customer relationship management.
a. True
b. False
3. Call center service training is a preproduction service that requires forecasts to create value in a value chain.
a. True
b. False
4. In the context of demand planning, customers’ wants and needs define the customer benefit package.
a. True
b. False
5. Judgmental forecasting relies upon historical data in developing forecasts.
a. True
b. False
6. A moving average (MA) method is most appropriate for data with major identifiable trends.
a. True
b. False
Indicate the answer choice that best completes the statement or answers the question.
7. In the context of forecasting, the term _____ refers to the tendency of forecasts to consistently be larger or smaller than
the actual values of the time series.
a. trend
b. bias
c. fad
d. variability
8. The mean square error (MSE) for the forecasts shown in the following table is:
Month Forecast Demand Actual Demand
April 170 180
May 225 200
June 210 200
July 260 240
August 200 230
a. more than 250 but less than or equal to 300.
b. more than 300 but less than or equal to 350.
c. more than 350 but less than or equal to 400.
Name:
Class:
Date:
chapter 9
d. more than 400 but less than or equal to 450.
9. Alex, a manager at Symbic Inc., plotted the company’s total energy costs of 1 billion dollars over the past 10 years on a
chart. The chart suggested that the energy costs appear to be increasing in a fairly predictable linear fashion and that the
energy costs are related to time by a linear function Yt =3+5t, where Yt represents the estimate of the energy cost in year t.
Given the equation, which of the following is the value of the intercept of the straight line that best fits the time series?
a. 1
b. 3
c. 5
d. 10
10. The following table shows the data for the sales of tennis rackets at a store for 4 consecutive months. Find the forecast
error in month 4 using a 3-month moving average.
Month 1 2 3 4
Sales 80 95 125 110
a. The forecast error in month 4 is less than or equal to 5.
b. The forecast error in month 4 is more than 5 but less than or equal to 10.
c. The forecast error in month 4 is more than 10 but less than or equal to 15.
d. The forecast error in month 4 is more than 15.
11. The mean absolute percentage error (MAPE) for the forecasts shown in the following table is:
Month Forecast Demand Actual Demand
April 110 100
May 150 125
June 160 170
July 110 130
August 150 180
a. less than or equal to 5 percent.
b. more than 5 percent but less than or equal to 10 percent.
c. more than 10 percent but less than or equal to 15 percent.
d. more than 15 percent.
12. _____ is a common approach to gather data for judgmental forecasts.
a. A moving average model
b. Regression analysis
c. A survey questionnaire
d. Single exponential smoothing
13. _____ is a forecasting technique that uses a weighted average of past time-series values to forecast the value of the
time series in the next period.
a. A moving average forecast
b. Single exponential smoothing
c. A grassroots forecast
d. Regression analysis
14. In the context of data patterns in a time series, a(n) _____ variation is a one-time variation that is explainable.
Name:
Class:
Date:
chapter 9
b. random
c. irregular
d. seasonal
15. A tracking signal provides a method for monitoring a forecast by quantifying _____.
a. bias
b. throughput
c. probability
d. validity
16. Moving average (MA) methods work best when:
a. a long planning horizon is involved.
b. a cyclical pattern is observed in a time series.
c. demand is relatively stable and consistent.
d. there is a major trend in a time series.
17. If the time series in an exponential smoothing model exhibits a negative trend, the _____.
a. mean square error will be negative
b. value of smoothing constant will either be less than zero or greater than one
c. forecast will overshoot the actual values
d. future forecasts will rely solely upon expertise of people in developing forecasts
18. When no historical data are available, _____ is the sole basis for predicting future demands.
a. statistical forecasting
b. regression analysis
c. judgmental forecasting
d. exponential smoothing
19. In the context of data patterns in a time series, _____ are characterized by repeatable periods of ups and downs over
short periods of time.
a. random variations
b. seasonal patterns
c. cyclical patterns
d. irregular variations
20. _____ is based on the assumption that the future will be an extrapolation of the past.
a. Judgmental forecasting
b. Statistical forecasting
c. The Delphi method
d. The Cooke method
21. The mean absolute deviation (MAD) for the forecasts shown in the following table is:
Month Forecast Demand Actual Demand
April 190 180
May 175 200
June 190 200
Name:
Class:
Date:
chapter 9
July 240 220
August 225 195
a. more than 10 but less than or equal to 20.
b. more than 20 but less than or equal to 30.
c. more than 30 but less than or equal to 40.
d. more than 40 but less than or equal to 50.
22. Forecast _____ is the difference between the observed value of the time series and the forecast.
a. error
b. consumption
c. precision
d. density
23. A _____ is the underlying pattern of growth or decline in a time series.
a. trend
b. planning horizon
c. forecast error
d. bias
24. In the Delphi method of judgmental forecasting, _____.
a. predictions are based on the assumption that the future will be an extrapolation of the past
b. predictions are based on one or more independent variables, all of which are numerical
c. people from outside an organization are not eligible to make predictions
d. experts are not consulted as a group to make predictions
25. An exponential smoothing model must have a smoothing constant (α) _____ to be roughly equivalent to a moving
average model with a seven-month moving average.
a. less than or equal to 0.10
b. more than 0.10 but less than or equal to 0.15
c. more than 0.15 but less than or equal to 0.20
d. more than 0.20
26. In the context of data patterns in a time series, regular patterns in a data series that take place over long periods of time
are called _____ patterns.
a. orthographic
b. seasonal
c. cyclical
d. parallel patterns
27. In the context of forecasting errors, _____ eliminates the measurement scale factor.
a. normalized mean signed deviation
b. mean absolute deviation
c. normalized root mean square error
d. mean absolute percentage error
Name:
Class:
Date:
chapter 9
28. In the context of a fairly stable time series with relatively little random variability, which of the following statements
is true of single exponential smoothing (SES)?
a. Values of the smoothing constant larger than 0.5 place more emphasis on recent data.
b. Exponential smoothing models completely forget past data if the smoothing constant is strictly between 0 and 1.
c. Typical values for the smoothing constant are in the range of 1 to 1.5.
d. Values of the smoothing constant smaller than 0.1 allow a forecast to react faster to changing conditions.
29. _____ is a method for building a statistical model that defines a relationship between a single dependent variable and
one or more independent variables, all of which are numerical.
a. The Delphi method
b. Regression analysis
c. Judgmental forecasting
d. The Cooke method
30. _____ are used by operations managers to plan production schedules and assign workers to jobs.
a. Balanced scorecards
b. Intermediate-range forecasts
c. Short-range forecasts
d. Credit scorecards
31. _____ are necessary to plan for facility expansion.
a. Long-range forecasts
b. Intermediate-range forecasts
c. Make-to-order operations
d. Make-to-stock operations
32. The following table shows the sales data of server computers of Ziffcore Inc. for the past 5 years. The management
plotted the data on a chart. The chart suggested that the sales appear to be increasing in a fairly predictable linear fashion
and that the sales are related to time by a linear function Yt =240+340t. Using simple linear regression, calculate the
forecast for sales in year 6.
Year Sales
1 580
2 920
3 1260
4 1600
5 1940
a. The forecast for sales in year 6 is more than 1800 but less than or equal to 2000.
b. The forecast for sales in year 6 is more than 2000 but less than or equal to 2200.
c. The forecast for sales in year 6 is more than 2200 but less than or equal to 2400.
d. The forecast for sales in year 6 is more than 2400 but less than or equal to 2600.
33. _____ are needed to plan workforce levels, allocate budgets among divisions, and schedule jobs and resources.
a. Make-to-order operations
b. Intermediate-range forecasts
c. Short-range forecasts
d. Make-to-stock operations
Name:
Class:
Date:
chapter 9
34. The following table shows the sales data of a particular model of a DVD player. If the forecast sales for May is 36.25,
calculate the sales forecast for July using the simple exponential smoothing (SES) model with a smoothing constant of
0.40.
Month Sales
Jan 35
Feb 29
Mar 39
Apr 42
May 51
Jun 56
a. The sales forecast for July is more than 30 but less than or equal to 35.
b. The sales forecast for July is more than 35 but less than or equal to 40.
c. The sales forecast for July is more than 40 but less than or equal to 50.
d. The sales forecast for July is more than 50 but less than or equal to 55.
35. The following table shows the data for the sales of a new music album at a store for 4 consecutive months. Find the
forecast for the next month using a 3-month moving average.
Month 1 2 3 4
Sales 112 105 125 118
a. The forecast for the next month is more than 90 but less than or equal to 100.
b. The forecast for the next month is more than 100 but less than or equal to 110.
c. The forecast for the next month is more than 110 but less than or equal to 120.
d. The forecast for the next month is more than 120 but less than or equal to 130.
Name:
Class:
Date:
chapter 9
Answer Key
Name:
Class:
Date:
chapter 9