Forecasting

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

C. Coefficient of Determination

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

C. Executive Opinion Model

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

A. Duration of the Repeating Pattern

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

A. Is Rather Stable

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

A. Naive Approach

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

A. Qualitative and Quantitive

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

A. Short-range, Medium-Range, and Long-Range

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

B. Economic, Technological and Demand

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.

B. Eliminating any assumptions

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

B. Medium-Range Forecast

Which of the following is not present in a time series? a. seasonality b. operational variations c. trend d. cycles e. random variations

B. Operational Variations

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

C. Long-Range Time Horizon

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

C. The Delphi Method

Gradual, long-term movement in time series data is called a. seasonal variation b. cycles c. trends d. exponential variation e. random variation

C. Trends

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

C. Weights each historical value equally

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

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

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

D. Correlation Coefficient

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

D. Exponential Smoothing

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.

D. Responsiveness to Change

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

D. random fluctuations

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

E. Exponentially smoothed forecast

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

E. Job Assignment

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

E. Moving Average

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.

E. They may exhibit all of the above.

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

b. are rarely perfect

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

c. measure forecast accuracy

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.

d. Exponential smoothing typically requires less record keeping of past data.

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.

e. Their values are determined independently.