Question 1

The mean absolute deviation is more sensitive to large deviations than the mean square error.

Accepted Answer

A) True 
 B)False  False

Question 2

Professor Z needs to allocate time among several tasks next week to include time for students' appointments. Thus, he needs to forecast the number of students who will seek appointments. He has gathered the following data:
$$\begin{array} { | c | c | } 
\hline \text { Week } & { \text { \# of students } } \
\hline 6 \text { weeks ago } & 85 \
\hline 5 \text { weeks ago } & 110 \
\hline 4 \text { weeks ago } & 95 \
\hline 3 \text { weeks ago } & 80 \
\hline 2 \text { weeks ago } & 65 \
\hline \text { Last week } & 50 \
\hline
\end{array}$$
What is the forecast for this year using the last-value forecasting method?

Accepted Answer

A)  49 
B)  50 
C)  52 
D)  65 
E)  78 
A)  49 
B)  50 
C)  52 
D)  65 
E)  78 B

Question 3

Given the following historical data, what is the moving-average forecast for period 6 based on the last three periods?
$$\begin{array} { | c | c | } 
\hline \text { Periud } & \text { Value } \
\hline 1 & 19 \
\hline 2 & 20 \
\hline 3 & 18 \
\hline 4 & 19 \
\hline 5 & 17 \
\hline
\end{array}$$

Accepted Answer

A)  17 
B)  18 
C)  19 
D)  20 
E)  18.5 
A)  17 
B)  18 
C)  19 
D)  20 
E)  18.5 B

Question 4

An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
$$\begin{array} { | c | c | } 
\hline \text { Year } & \text { \# Sald } \
\hline 4 \text { years ago } & 10,000 \
\hline 3 \text { years ago } & 12,000 \
\hline \text { 2 years ago } & 18,000 \
\hline \text { Last year } & 20,000 \
\hline
\end{array}$$
The previous trend line has predicted 18,500 for two years ago, and 19,700 for last year. What was the mean absolute deviation for these forecasts?

Accepted Answer

A)  100 
B)  200 
C)  400 
D)  500 
E)  800 
A)  100 
B)  200 
C)  400 
D)  500 
E)  800

Question 5

Time-series data may exhibit which of the following behaviors?

Accepted Answer

A)  Trend 
B)  Seasonality 
C)  Cycles 
D)  Irregularities 
E)  All of the answers choices are correct 
A)  Trend 
B)  Seasonality 
C)  Cycles 
D)  Irregularities 
E)  All of the answers choices are correct

Question 6

The sales force composite method is a top-down approach to forecasting.

Accepted Answer

A) True 
 B)False

Question 7

The goal of time-series forecasting methods is to estimate the mean of the underlying probability distribution of the next value of the time-series as closely as possible.

Accepted Answer

A) True 
 B)False

Question 8

The president of State University wants to forecast student enrollment for this academic year based on the following historical data:
$$\begin{array} { | c | c | } 
\hline \text { Year } & \text { Enrollnents } \
\hline 5 \text { years ago } & 15,000 \
\hline 4 \text { years ago } & 16,000 \
\hline 3 \text { years ago } & 18,000 \
\hline \text { 2 years ago } & 20,000 \
\hline \text { Luast year } & 21,000 \
\hline
\end{array}$$
What is the forecast for this year using exponential smoothing with ? = 0.5, if the forecast for two years ago was 16,000?

Accepted Answer

A)  18,750 
B)  19,500 
C)  21,000 
D)  22,650 
E)  22,800 
A)  18,750 
B)  19,500 
C)  21,000 
D)  22,650 
E)  22,800

Question 9

Professor Z needs to allocate time among several tasks next week to include time for students' appointments. Thus, he needs to forecast the number of students who will seek appointments. He has gathered the following data:
$$\begin{array} { | c | c | } 
\hline \text { Week } & { \text { \# of students } } \
\hline 6 \text { weeks ago } & 85 \
\hline 5 \text { weeks ago } & 110 \
\hline 4 \text { weeks ago } & 95 \
\hline 3 \text { weeks ago } & 80 \
\hline 2 \text { weeks ago } & 65 \
\hline \text { Last week } & 50 \
\hline
\end{array}$$
What is the forecast for this year using a moving-average forecast based on the last three weeks?

Accepted Answer

A)  49 
B)  50 
C)  52 
D)  65 
E)  78 
A)  49 
B)  50 
C)  52 
D)  65 
E)  78

Question 10

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

Accepted Answer

A)  Managerial opinion 
B)  Sales force composite 
C)  Time-series analysis 
D)  The Delphi method 
E)  Consumer market survey 
A)  Managerial opinion 
B)  Sales force composite 
C)  Time-series analysis 
D)  The Delphi method 
E)  Consumer market survey

Question 11

The last-value forecasting method is most useful when conditions are stable over time.

Accepted Answer

A) True 
 B)False

Question 12

Given forecast errors of 5, 0, −4, and 3, what is the mean square error?

Accepted Answer

A)  3 
B)  4 
C)  12 
D)  12.5 
E)  50 
A)  3 
B)  4 
C)  12 
D)  12.5 
E)  50

Question 13

The last-value forecasting method requires a linear trend line.

Accepted Answer

A) True 
 B)False

Question 14

An operation analyst is forecasting this year's demand for one of his company's products based on the following historical data:
$$\begin{array} { | c | c | } 
\hline \text { Year } & \text { \# Sald } \
\hline 4 \text { years ago } & 10,000 \
\hline 3 \text { years ago } & 12,000 \
\hline \text { 2 years ago } & 18,000 \
\hline \text { Last year } & 20,000 \
\hline
\end{array}$$
What is the forecast for this year using a moving-average forecast based on the last four years?

Accepted Answer

A)  22,000 
B)  20,000 
C)  18,000 
D)  15,000 
E)  12,000 
A)  22,000 
B)  20,000 
C)  18,000 
D)  15,000 
E)  12,000

Question 15

Forecasting techniques such as moving-average, exponential smoothing, and the last-value method all represent averaged values of time-series data.

Accepted Answer

A) True 
 B)False

Question 16

Linear regression can be used to approximate the relationship between independent and dependent variables.

Accepted Answer

A) True 
 B)False

Question 17

A manager uses the equation y = 40,000 + 150x to predict monthly receipts. What is the forecast for July if x = 0 in April?

Accepted Answer

A)  40,450 
B)  40,600 
C)  42,100 
D)  42,250 
E)  42,400 
A)  40,450 
B)  40,600 
C)  42,100 
D)  42,250 
E)  42,400

Question 18

Given forecast errors of 5, 0, −4, and 3, what is the mean absolute deviation?

Accepted Answer

A)  1 
B)  2 
C)  2.5 
D)  3 
E)  12 
A)  1 
B)  2 
C)  2.5 
D)  3 
E)  12

Question 19

Which of the following would be considered a possible drawback of using executive opinions to develop a forecast?

Accepted Answer

A)  It is difficult to interpret the results. 
B)  Responsibility is diffused for the forecast. 
C)  Extensive use of computers is needed. 
D)  It brings together the knowledge of top managers. 
E)  Forecasters are sometimes overly influenced by recent events. 
A)  It is difficult to interpret the results. 
B)  Responsibility is diffused for the forecast. 
C)  Extensive use of computers is needed. 
D)  It brings together the knowledge of top managers. 
E)  Forecasters are sometimes overly influenced by recent events.

Question 20

Exponential smoothing with trend was designed for time-series that have great variability both up and down.

Accepted Answer

A) True 
 B)False

The mean absolute deviation is more sensitive to large deviations than the mean square error.

Given the following historical data, what is the moving-average forecast for period 6 based on the last three periods? Periud Value 1 19 2 20 3 18 4 19 5 17

Time-series data may exhibit which of the following behaviors?

The sales force composite method is a top-down approach to forecasting.

The goal of time-series forecasting methods is to estimate the mean of the underlying probability distribution of the next value of the time-series as closely as possible.

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

The last-value forecasting method is most useful when conditions are stable over time.

Given forecast errors of 5, 0, −4, and 3, what is the mean square error?

The last-value forecasting method requires a linear trend line.

Forecasting techniques such as moving-average, exponential smoothing, and the last-value method all represent averaged values of time-series data.

Linear regression can be used to approximate the relationship between independent and dependent variables.

A manager uses the equation y = 40,000 + 150x to predict monthly receipts. What is the forecast for July if x = 0 in April?

Given forecast errors of 5, 0, −4, and 3, what is the mean absolute deviation?

Which of the following would be considered a possible drawback of using executive opinions to develop a forecast?

Exponential smoothing with trend was designed for time-series that have great variability both up and down.

Introduction

Linear Programming: Basic Concepts

Linear Programming: Formulation and Applications

The Art of Modeling With Spreadsheets

What-If Analysis for Linear Programming

Network Optimization Problems

Using Binary Integer Programming to Deal With Yes-Or-No Decisions

Nonlinear Programming

Decision Analysis

Queueing Models

Computer Simulation: Basic Concepts

Computer Simulation With Analytic Solver

Filters

Exam 10: Forecasting

The mean absolute deviation is more sensitive to large deviations than the mean square error.

Given the following historical data, what is the moving-average forecast for period 6 based on the last three periods? Periud Value 1 19 2 20 3 18 4 19 5 17

Time-series data may exhibit which of the following behaviors?

The sales force composite method is a top-down approach to forecasting.

The goal of time-series forecasting methods is to estimate the mean of the underlying probability distribution of the next value of the time-series as closely as possible.

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

The last-value forecasting method is most useful when conditions are stable over time.

Given forecast errors of 5, 0, −4, and 3, what is the mean square error?

The last-value forecasting method requires a linear trend line.

Forecasting techniques such as moving-average, exponential smoothing, and the last-value method all represent averaged values of time-series data.

Linear regression can be used to approximate the relationship between independent and dependent variables.

A manager uses the equation y = 40,000 + 150x to predict monthly receipts. What is the forecast for July if x = 0 in April?

Given forecast errors of 5, 0, −4, and 3, what is the mean absolute deviation?

Which of the following would be considered a possible drawback of using executive opinions to develop a forecast?

Exponential smoothing with trend was designed for time-series that have great variability both up and down.

Introduction

Linear Programming: Basic Concepts

Linear Programming: Formulation and Applications

The Art of Modeling With Spreadsheets

What-If Analysis for Linear Programming

Network Optimization Problems

Using Binary Integer Programming to Deal With Yes-Or-No Decisions

Nonlinear Programming

Decision Analysis

Queueing Models

Computer Simulation: Basic Concepts

Computer Simulation With Analytic Solver

Filters