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Forecasts
a. become more accurate with longer time horizons
b. are rarely perfect
c. are more accurate for individual items than for groups of items
d. all of the above
e. none of the above
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b. are rarely perfect
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One use of short-range forecasts is to determine
a. production planning
b. inventory budgets
c. research and development plans
d. facility location
e. job assignments
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E. Job Assignment
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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
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A. Short-range, Medium-Range, and Long-Range
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A forecast with a time horizon of about 3 months to 3 years is typically called a
a. long-range forecast
b. medium-range forecast
c. short-range forecast
d. weather forecast
e. strategic forecast
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B. Medium-Range Forecast
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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
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C. Long-Range Time Horizon
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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
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B. Economic, Technological and Demand
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Which of the following is not a step in the forecasting process?
a. Determine the use of the forecast.
b. Eliminate any assumptions.
c. Determine the time horizon.
d. Select forecasting model.
e. Validate and implement the results.
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B. Eliminating any assumptions
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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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A. Qualitative and Quantitive
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Which of the following uses three types of participants: decision makers, staff personnel, and
respondents?
a. executive opinions
b. sales force composites
c. the Delphi method
d. consumer surveys
e. time series analysis
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C. The Delphi Method
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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
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C. Executive Opinion Model
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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
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E. Moving Average
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Time series data may exhibit which of the following behaviors?
a. trend
b. random variations
c. seasonality
d. cycles
e. They may exhibit all of the above.
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E. They may exhibit all of the above.
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Gradual, long-term movement in time series data is called
a. seasonal variation
b. cycles
c. trends
d. exponential variation
e. random variation
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C. Trends
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Which of the following is not present in a time series?
a. seasonality
b. operational variations
c. trend
d. cycles
e. random variations
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B. Operational Variations
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The fundamental difference between cycles and seasonality is the
a. duration of the repeating patterns
b. magnitude of the variation
c. ability to attribute the pattern to a cause
d. all of the above
e. none of the above
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A. Duration of the Repeating Pattern
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In time series, which of the following cannot be predicted?
a. large increases in demand
b. technological trends
c. seasonal fluctuations
d. random fluctuations
e. large decreases in demand
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D. random fluctuations
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Which time series model below assumes that demand in the next period will be equal to the most
recent period’s demand?
a. naive approach
b. moving average approach
c. weighted moving average approach
d. exponential smoothing approach
e. none of the above
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A. Naive Approach
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A six-month moving average forecast is better than a three-month moving average forecast if
demand
a. is rather stable
b. has been changing due to recent promotional efforts
c. follows a downward trend
d. follows a seasonal pattern that repeats itself twice a year
e. follows an upward trend
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A. Is Rather Stable
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Increasing the number of periods in a moving average will accomplish greater smoothing, but at
the expense of
a. manager understanding
b. accuracy
c. stability
d. responsiveness to changes
e. All of the above are diminished when the number of periods increases.
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D. Responsiveness to Change
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Which of the following statements comparing the weighted moving average technique and
exponential smoothing is true?
a. Exponential smoothing is more easily used in combination with the Delphi method.
b. More emphasis can be placed on recent values using the weighted moving average.
c. Exponential smoothing is considerably more difficult to implement on a computer.
d. Exponential smoothing typically requires less record keeping of past data.
e. Exponential smoothing allows one to develop forecasts for multiple periods, whereas weighted
moving averages does not.
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d. Exponential smoothing typically requires less record keeping of past data.
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Which time series model uses past forecasts and past demand data to generate a new forecast?
a. naive
b. moving average
c. weighted moving average
d. exponential smoothing
e. regression analysis
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D. Exponential Smoothing
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Which is not a characteristic of exponential smoothing?
a. smoothes random variations in the data
b. easily altered weighting scheme
c. weights each historical value equally
d. has minimal data storage requirements
e. none of the above; they are all characteristics of exponential smoothing
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C. Weights each historical value equally
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A forecast based on the previous forecast plus a percentage of the forecast error is a(n)
a. qualitative forecast
b. naive forecast
c. moving average forecast
d. weighted moving average forecast
e. exponentially smoothed forecast
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E. Exponentially smoothed forecast
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The primary purpose of the mean absolute deviation (MAD) in forecasting is to
a. estimate the trend line
b. eliminate forecast errors
c. measure forecast accuracy
d. seasonally adjust the forecast
e. all of the above
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c. measure forecast accuracy
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Which of the following is true regarding the two smoothing constants of the Forecast Including
Trend (FIT) model?
a. One constant is positive, while the other is negative.
b. They are called MAD and RSFE.
c. Alpha is always smaller than beta.
d. One constant smoothes the regression intercept, whereas the other smoothes the regression
slope.
e. Their values are determined independently.
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e. Their values are determined independently.
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A fundamental distinction between trend projection and linear regression is that
a. trend projection uses least squares while linear regression does not
b. only linear regression can have a negative slope
c. in trend projection the independent variable is time; in linear regression the independent
variable need not be time, but can be any variable with explanatory power
d. linear regression tends to work better on data that lack trends
e. trend projection uses two smoothing constants, not just one
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C. in trend projection the independent variable is time; in linear regression the independent variable need not be time, but can be any variable with explanatory power
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The percent of variation in the dependent variable that is explained by the regression equation is
measured by the
a. mean absolute deviation
b. slope
c. coefficient of determination
d. correlation coefficient
e. intercept
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C. Coefficient of Determination
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The degree or strength of a linear relationship is shown by the
a. alpha
b. mean
c. mean absolute deviation
d. correlation coefficient
e. RSFE
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D. Correlation Coefficient
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