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Exam 3: Forecasting

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Question 21

True/False

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

A) True
B) False

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Question 22

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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: What is this year's forecast using the naive approach?

A) 2,000
B) 2,200
C) 2,800
D) 3,000
E) 3,200

F) All of the above
G) D) and E)

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Question 23

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Suppose a four-period weighted average is being used to forecast demand. Weights for the periods are as follows: w _t-4 = 0.1, w _t-3 = 0.2, w _t-2 = 0.3 and w _t-1 = 0.4. Demand observed in the previous four periods was as follows: A _t-4 = 380, A _t-3 = 410, A _t-2 = 390, and A _t-1 = 400. What will be the demand forecast for period t?

Once accepted by managers, forecasts should be held firm regardless of new input since many plans have been made using the original forecast.

Which of the following is the most valuable piece of information the sales force can bring into forecasting situations?

Forecasts based on an average tend to exhibit less variability than the original data.

The naive approach to forecasting requires a linear trend line.

When choosing a forecasting technique, a critical trade-off that must be considered is that between:

Forecasting techniques generally assume an existing causal system that will continue to exist in the future.

Putting forecast errors into perspective is best done using

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

The business analyst for Video Sales, Inc. wants to forecast this year's demand for DVD decoders based on the following historical data: What is the forecast for this year using exponential smoothing with alpha = 0.4, if the forecast for two years ago was 750?

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 exponential smoothing with alpha = 0.2, if the forecast for two weeks ago was 90?

Exponential smoothing is a form of weighted averaging.

Given an actual demand of 105, a forecasted value of 97, and an alpha of 0.4, the simple exponential smoothing forecast for the next period would be:

The owner of Darkest Tans Unlimited in a local mall is forecasting this month's (October's) demand for the one new tanning booth based on the following historical data: What is this month's forecast using a four-month weighted moving average with weights of 0.4, 0.3, 0.2, and 0.1?

In exponential smoothing, an alpha of 1.0 will generate the same forecast that a naive forecast would yield.

In order to update a moving average forecast, the values of each data point in the average must be known.

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

Averaging techniques are useful for: