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Exam 3: Forecasting

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Question 51

Multiple Choice

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

A) estimate of accuracy
B) timeliness
C) meaningful units
D) low cost
E) written

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

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Question 52

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The naive forecast is limited in its application to series that reflect no trend or seasonality.

A) True
B) False

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Question 53

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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: $\begin{array} { l l } \text { Week } & \text { \# Students } \\\hline 6 \text { weeks ago } & 83 \\5 \text { weeks ago } & 110 \\4 \text { weeks ago } & 95 \\3 \text { weeks ago } & 80 \\2 \text { weeks ago } & 65 \\\text { Last week } & 50\end{array}$ What is this week's forecast using the naive approach?

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 naive approach?

Exponential smoothing is a form of weighted averaging.

The president of State University wants to forecast student enrollments for this academic year based on the following historical data: $\begin{array} { l l } \text { Year } & \text { Enrollments } \\\hline \text { 5 years ago } & 15,000 \\4 \text { years ago } & 16,000 \\\text { 3 years ago } & 18,000 \\2 \text { years ago } & 20,000 \\\text { Last year } & 21,000\end{array}$ What is the forecast for this year using exponential smoothing with alpha = .5, if the forecast for two years ago was 16,000?

Forecasting techniques that are based on time-series data assume that future values of the series will duplicate past values.

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: $\begin{array} { l l } \text { Week } & \text { \# Students } \\\hline 6 \text { weeks ago } & 83 \\5 \text { weeks ago } & 110 \\4 \text { weeks ago } & 95 \\3 \text { weeks ago } & 80 \\2 \text { weeks ago } & 65 \\\text { Last week } & 50\end{array}$ What is this week's forecast using exponential smoothing with alpha = .2, if the forecast for two weeks ago was 90?

A forecast method is generally deemed to perform adequately when the errors exhibit an identifiable pattern.

Use of simple linear regression analysis assumes that:

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: $\begin{array} { l l } \text { Year } & \text { Enrollment } \\\hline \text { Four years ago } & 2000 \\\text { Three years ago } & 2200 \\\text { Two years ago } & 2800 \\\text { Last year } & 3000\end{array}$ What is this year's forecast using exponential smoothing with alpha = .4, if last year's smoothed forecast was 2,600?

If a pattern appears when a dependent variable is plotted against time, one should use time series analysis instead of regression analysis.

The degree of management involvement in short-range forecasts is:

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: $\begin{array} { l l } \text { Year } & \text { Enrollment } \\\hline \text { Four years ago } & 2000 \\\text { Three years ago } & 2200 \\\text { Two years ago } & 2800 \\\text { Last year } & 3000\end{array}$ What is the annual rate of change (slope) of the least squares trend line for these data?

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 centered moving average for spring two years ago?

Develop a linear trend equation for the data on bread deliveries shown below. Forecast deliveries for period 11 through 14. $\begin{array} { l l } \text { Period } & \text { Deliveries (dozens) } \\\hline 1 & 648 \\2 & 590 \\3 & 631 \\4 & 769 \\5 & 745 \\6 & 856 \\7 & 760 \\8 & 962 \\9 & 990 \\10 & 1100\end{array}$

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

Given the data below, develop a forecast for period 6 using a four-period weighted moving average and weights of .4, .3, .2 and .1. $\begin{array} { l l } \text { Period } & \text { Demand } \\\hline 1 & 19 \\2 & 20 \\3 & 18 \\4 & 19 \\5 & 17\end{array}$

Which of the following possible values of alpha would cause exponential smoothing to respond the most quickly to forecast errors?

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: $\begin{array} { l l } \text { Week } & \text { \# Students } \\\hline 6 \text { weeks ago } & 83 \\5 \text { weeks ago } & 110 \\4 \text { weeks ago } & 95 \\3 \text { weeks ago } & 80 \\2 \text { weeks ago } & 65 \\\text { Last week } & 50\end{array}$ What is this week's forecast using the least squares trend line for these data?