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Exam 3: Demand Forecasting

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Question 21

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Which of the following is not a type of judgmental forecasting?

A) Executive opinions
B) Sales force opinions
C) Consumer surveys
D) Expert opinions
E) Time series analysis

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Question 22

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Naive forecasting methods:

A) are quick and easy to prepare.
B) are easy for users to understand.
C) can serve as an accuracy standard for other techniques.
D) All of the choices are true.
E) None of the choices are true.

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Question 23

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In exponential smoothing,an alpha of .30 will cause a forecast to react more quickly to a large error than will an alpha of .20.

Positive forecast errors mean that the forecast:

As a forecasting technique,the Delphi technique is useful for technological forecasting.

-What is the linear regression trend line for these data (t = 1 for spring,three years ago)?

What is the forecast for this year using trend adjusted (double) smoothing with alpha(1) = 0.3 and alpha(2) = 0.2,if the forecast for last year was 31,the forecast for two years ago was 43,and the trend estimate for last year's forecast was -15?

What is this week's forecast using trend adjusted (double) smoothing with alpha(1) = 0.5 and alpha(2) = 0.1,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?

Increasing the number of data points included in a moving average will result in a forecast that is smoother but less responsive to changes.

Forecasts based on time series (historical)data are referred to as associative forecasts.

Which is not a characteristic of exponential smoothing?

What is the annual rate of change (slope) of the least squares trend line for these data?

A manager has been using a certain technique to forecast demand for units of web publishing software for the past six periods.Actual and predicted amounts are shown below.Would a naive forecast have produced better results?

A seasonal relative (or seasonal indexes)is expressed as a percentage of the average or trend in a time series.

What is this year's forecast using the least squares trend line for these data?

-What is the seasonal relative for each season?

An automobile company is trying to forecast demand for minivans over the next 10 years.Which method of forecasting are they most likely to use?

What is this month's forecast using the naive approach?

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

Removing the seasonal component from a data series (deseasonalizing)can be accomplished by dividing each data point by its appropriate seasonal relative.