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Exam 3: Forecasting

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Question 41

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A consumer survey is an easy and sure way to obtain accurate input from future customers since most people enjoy participating in surveys.

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B) False

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Question 42

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The shorter the forecast period, the more accurately the forecasts tend to track what actually happens.

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Question 43

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The business analyst for Video Sales, Inc. wants to forecast this year's demand for DVD decoders based on the following historical data: $\begin{array} { | c | c | } \hline \text { Year } & \text { Demand } \\\hline \text { 5 Years ago } & 900 \\\hline \text { 4 Years ago } & 700 \\\hline 3 \text { Years ago } & 600 \\\hline \text { 2 Years ago } & 500 \\\hline \text { Last Year } & 300 \\\hline\end{array}$ What is the forecast for this year using the naive approach?

Gradual, long-term movement in time series data is called:

Bias is measured by the ratio of the cumulative sum of forecast errors to the mean absolute deviation (MAD).

Which is not a characteristic of simple moving averages applied to time series data?

Trend-adjusted exponential smoothing requires selection of two smoothing constants.

Given forecast errors of 4, 8, and -3, what is the mean absolute deviation?

Which of the following is not a step in the forecasting process?

An advantage of a weighted moving average is that recent actual results can be given more importance than what occurred a while ago.

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

The business analyst for Video Sales, Inc. wants to forecast this year's demand for DVD decoders based on the following historical data: $\begin{array} { | l | c | } \hline{ \text { Year } } & \text { Enrollments } \\\hline \text { 5 Years ago } & 900 \\\hline \text { 4 Years ago } & 700 \\\hline \text { 3 Years ago } & 600 \\\hline \text { 2 Years ago } & 500 \\\hline \text { Last Year } & 300 \\\hline\end{array}$ What is the forecast for this year using exponential smoothing with alpha = .4, if the forecast for two years ago was 750?

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

Forecasting techniques generally assume:

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

Which is not a characteristic of exponential smoothing?

Exponential smoothing adds a percentage (called alpha) of the last period's forecast to estimate the next period's demand.

Use of simple linear regression analysis assumes that:

The business analyst for Video Sales, Inc. wants to forecast this year's demand for DVD decoders based on the following historical data: $\begin{array} { | l | c | } \hline \text { Year } & \text { Enrollments } \\\hline \text { 5 Years ago } & 900 \\\hline \text { 4 Years ago } & 700 \\\hline \text { 3 Years ago } & 600 \\\hline \text { 2 Years ago } & 500 \\\hline \text { Last Year } & 300 \\\hline\end{array}$ What is the forecast for this year using the least squares trend line for these data?

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 exponential smoothing with alpha = .2, if last year's smoothed forecast was 15,000?