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Exam 3: Forecasting

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Question 21

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The two most important factors in choosing a forecasting technique are:

A)  cost and time horizon.
B)  accuracy and time horizon.
C)  cost and accuracy.
D)  quantity and quality.
E)  objective and subjective components.

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Question 22

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The sample standard deviation of forecast error is estimated by the square root of MSE.

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Question 23

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A smoothing constant of .1 will cause an exponential smoothing forecast to react more quickly to a sudden change than a smoothing constant value of .3.

Which of the following corresponds to the predictor variable in simple linear regression?

Which of the following would be an advantage of using a sales force composite to develop a demand forecast?

Which of the following features would not generally be considered common to all forecasts?

The primary method for associative forecasting is:

Which of the following is not necessarily an element of a good forecast?

The dean of a school of business is forecasting total student enrollment for this year's summer session classes based on the following historical data: $\begin{array} { | l | c | } \hline { \text { Year } } & \text { Enrollment } \\\hline \text { Four years ago } & 2000 \\\hline \text { Three years ago } & 2200 \\\hline \text { Two years ago } & 2800 \\\hline \text { Last year } & 3000 \\\hline\end{array}$ What is this year's forecast using exponential smoothing with alpha = .4, if last year's smoothed forecast was 2,600?

The best forecast is not necessarily the most accurate.

A concert promoter is forecasting this year's attendance for one of his concerts based on the following historical data: $\begin{array} { | l | c | } \hline { \text { Year } } & \text { Attendance } \\\hline \text { Four Years ago } & 10,000 \\\hline \text { Three Years ago } & 12,000 \\\hline \text { Two Years ago } & 18,000 \\\hline \text { Last Year } & 20,000 \\\hline\end{array}$ What is this year's forecast using the naive approach?

In the additive model for seasonality, seasonality is expressed as a ______________ adjustment to the average; in the multiplicative model, seasonality is expressed as a __________ adjustment to the average.

A tracking signal focuses on the ratio of cumulative forecast error to the corresponding value of MAD.

Which of the following mechanisms for enhancing profitability is most likely to result from improving short-term forecast performance?

The dean of a school of business is forecasting total student enrollment for this year's summer session classes based on the following historical data: $\begin{array} { | l | c | } \hline { \text { Year } } & \text { Enrollment } \\\hline \text { Four years ago } & 2000 \\\hline \text { Three years ago } & 2200 \\\hline \text { Two years ago } & 2800 \\\hline \text { Last year } & 3000 \\\hline\end{array}$ What is the annual rate of change (slope) of the least squares trend line for these data?

In order to compute seasonal relatives, the trend of past data must be computed or known, which means that for brand-new products this approach cannot be used.

Which phrase most closely describes the Delphi technique?

Simple exponential smoothing is being used to forecast demand. The previous forecast of 66 turned out to be four units less than actual demand. The next forecast is 66.6, implying a smoothing constant, alpha, equal to:

Professor Very Busy needs to allocate time next week to include time for office hours. He needs to forecast the number of students who will seek appointments. He has gathered the following data: What is this week's forecast using trend-adjusted (double) smoothing with alpha = .5 and beta = .1, if the forecast for last week was 65, the forecast for two weeks ago was 75, and the trend estimate for last week's forecast was -5?

Given forecast errors of 5, 0, -4, and 3, what is the tracking signal?