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Exam 3: Forecasting

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Question 81

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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: $\begin{array} { l l } \text { Month } & \text { Number of Visits } \\\hline \text { April } & 100 \\\text { May } & 140 \\\text { June } & 110 \\\text { July } & 150 \\\text { August } & 120 \\\text { September } & 160\end{array}$ What is this month's forecast using the least squares trend line for these data?

A) 1,250
B) 128.6
C) 102
D) 158
E) 164

F) B) and E)
G) D) and E)

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Question 82

Multiple Choice

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Moving average forecasting techniques do the following:

A) Immediately reflect changing patterns in the data.
B) Lead changes in the data.
C) Smooth variations in the data.
D) Operate independently of recent data.
E) Assist when organizations are relocating.

F) B) and E)
G) None of the above

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Question 83

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Detecting nonrandomness in errors can be done using:

Which of the following is/are a primary input into capacity, sales, and production planning?

Data on the last three years of demand are available as follows: $\begin{array} { l l l l l } &&& { \text { Season } } \\\text { Year } & \text { Spring } & \text { Summer } & \text { Fall } & \text { Winter } \\\hline \text { Three years ago } & 18 & 10 & 26 & 42 \\\text { Two years ago } & 26 & 18 & 34 & 50 \\\text { Last year } & 34 & 26 & 42 & 58\end{array}$ What is the spring's seasonal relative?

In order to increase the responsiveness of a forecast made using the moving average technique, the number of data points in the average should be:

A concert promoter is forecasting this year's attendance for one of his concerts based on the following historical data: $\begin{array} { l l } \text { Year } & \text { Attendance } \\\hline \text { Four years ago } & 10,000 \\\text { Three years ago } & 12,000 \\\text { Two years ago } & 18,000 \\\text { Last Year } & 20,000\end{array}$ What is this year's forecast using a two-year weighted moving average with weights of .7 and .3?

The use of a control chart assumes that errors are normally distributed about a mean of zero.

A concert promoter is forecasting this year's attendance for one of his concerts based on the following historical data: $\begin{array} { l l } \text { Year } & \text { Attendance } \\\hline \text { Four years ago } & 10,000 \\\text { Three years ago } & 12,000 \\\text { Two years ago } & 18,000 \\\text { Last Year } & 20,000\end{array}$ The previous trend line had predicted 18,500 for two years ago, and 19,700 for last year. What was the mean absolute deviation for these forecasts?

Using the latest observation in a sequence of data to forecast the next period is:

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:

In trend-adjusted exponential smoothing, the trend-adjusted forecast consists of:

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.

Which phrase most closely describes the Delphi technique?

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

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

Which of the following is used for constructing a control chart?

Data on demand over the last few years are available as follows: $\begin{array} { l l } \text { Time Period } & \text { Demand } \\\hline 7 \text { years ago } & 7 \\6 \text { years ago } & 28 \\\text { 5 years ago } & 21 \\\text { 4 years ago } & 42 \\\text { 3 years ago } & 35 \\\text { 2 years ago } & 56 \\\text { Last year } & 49\end{array}$ What is this year's forecast using trend-adjusted (double) smoothing with alpha = .2 and beta = .1, if the forecast for last year was 56, the forecast for two years ago was 46, and the trend estimate for last year's forecast was 7?

Bias exists when forecasts tend to be greater or less than the actual values of time series.

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: $\begin{array} { l l } \text { Month } & \text { Number of Visits } \\\hline \text { April } & 100 \\\text { May } & 140 \\\text { June } & 110 \\\text { July } & 150 \\\text { August } & 120 \\\text { September } & 160\end{array}$ What is this month's forecast using exponential smoothing with alpha = .2, if August's forecast was 145?