Question 1

Forecasts of future demand are used by operations people to plan capacity.

Accepted Answer

A) True 
 B)False

Question 2

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

Accepted Answer

A) True 
 B)False

Question 3

When new products or services are introduced, focus forecasting models are an attractive option.

Accepted Answer

A) True 
 B)False

Question 4

Minimizing the sum of the squared deviations around the line is called:

Accepted Answer

A)  mean squared error technique. 
B)  mean absolute deviation. 
C)  double smoothing. 
D)  least squares estimation. 
E)  predictor regression. 
A)  mean squared error technique. 
B)  mean absolute deviation. 
C)  double smoothing. 
D)  least squares estimation. 
E)  predictor regression.

Question 5

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

Accepted Answer

A) True 
 B)False

Question 6

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

Accepted Answer

A)  time series and associative. 
B)  seasonality and cyclicality. 
C)  length and duration. 
D)  simplicity and complexity. 
E)  cost and accuracy. 
A)  time series and associative. 
B)  seasonality and cyclicality. 
C)  length and duration. 
D)  simplicity and complexity. 
E)  cost and accuracy.

Question 7

A concert promoter is forecasting this year's attendance for one of his concerts based on the following historical data: $$\begin{array} { | l | c | } 
\hline { \text { Year } } & \text { Attendance } \
\hline \text { Four Years ago } & 10,000 \
\hline \text { Three Years ago } & 12,000 \
\hline \text { Two Years ago } & 18,000 \
\hline \text { Last Year } & 20,000 \
\hline
\end{array}$$
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?

Accepted Answer

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

Question 8

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

Accepted Answer

A) True 
 B)False

Question 9

Detecting nonrandomness in errors can be done using:

Accepted Answer

A)  MSEs. 
B)  MAPs. 
C)  control charts. 
D)  correlation coefficients. 
E)  strategies. 
A)  MSEs. 
B)  MAPs. 
C)  control charts. 
D)  correlation coefficients. 
E)  strategies.

Question 10

The business analyst for Video Sales, Inc. wants to forecast this year's demand for DVD decoders based on the following historical data: $$\begin{array} { | l | c | } 
\hline \text { Year } & \text { Enrollments } \
\hline \text { 5 Years ago } & 900 \
\hline \text { 4 Years ago } & 700 \
\hline \text { 3 Years ago } & 600 \
\hline 2 \text { Years ago } & 500 \
\hline \text { Last Year } & 300 \
\hline
\end{array}$$
What is the forecast for this year using a three-year weighted moving average with weights of .5, .3, and .2?

Accepted Answer

A)  163 
B)  180 
C)  300 
D)  420 
E)  510 
A)  163 
B)  180 
C)  300 
D)  420 
E)  510

Question 11

Which technique is used in computing seasonal relatives?

Accepted Answer

A)  double smoothing 
B)  Delphi 
C)  mean squared error 
D)  centered moving average 
E)  exponential smoothing 
A)  double smoothing 
B)  Delphi 
C)  mean squared error 
D)  centered moving average 
E)  exponential smoothing

Question 12

The naive approach to forecasting requires a linear trend line.

Accepted Answer

A) True 
 B)False

Question 13

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

Accepted Answer

A) True 
 B)False

Question 14

Accuracy in forecasting can be measured by:

Accepted Answer

A)  MSE. 
B)  MRP. 
C)  MPS. 
D)  MTM. 
E)  MTE. 
A)  MSE. 
B)  MRP. 
C)  MPS. 
D)  MTM. 
E)  MTE.

Question 15

Seasonal relatives can be used to deseasonalize data or incorporate seasonality in a forecast.

Accepted Answer

A) True 
 B)False

Question 16

A managerial approach toward forecasting which seeks to actively influence demand is:

Accepted Answer

A)  reactive. 
B)  proactive. 
C)  influential. 
D)  protracted. 
E)  retroactive. 
A)  reactive. 
B)  proactive. 
C)  influential. 
D)  protracted. 
E)  retroactive.

Question 17

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 the least squares trend line for these data?

Accepted Answer

A)  20,000 
B)  21,000 
C)  22,000 
D)  23,000 
E)  24,000 
A)  20,000 
B)  21,000 
C)  22,000 
D)  23,000 
E)  24,000

Question 18

The purpose of the forecast should be established first so that the level of detail, amount of resources, and accuracy level can be understood.

Accepted Answer

A) True 
 B)False

Question 19

Forecasts for groups of items tend to be less accurate than forecasts for individual items because forecasts for individual items don't include as many influencing factors.

Accepted Answer

A) True 
 B)False

Question 20

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

Accepted Answer

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

Exam 3: Forecasting

Forecasts of future demand are used by operations people to plan capacity.

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

When new products or services are introduced, focus forecasting models are an attractive option.

Minimizing the sum of the squared deviations around the line is called:

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

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

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

Detecting nonrandomness in errors can be done using:

Which technique is used in computing seasonal relatives?

The naive approach to forecasting requires a linear trend line.

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

Accuracy in forecasting can be measured by:

Seasonal relatives can be used to deseasonalize data or incorporate seasonality in a forecast.

A managerial approach toward forecasting which seeks to actively influence demand is:

A concert promoter is forecasting this year's attendance for one of his concerts based on the following historical data: Year Attendance Four Years ago 10,000 Three Years ago 12,000 Two Years ago 18,000 Last Year 20,000 What is this year's forecast using the least squares trend line for these data?

The purpose of the forecast should be established first so that the level of detail, amount of resources, and accuracy level can be understood.

Forecasts for groups of items tend to be less accurate than forecasts for individual items because forecasts for individual items don't include as many influencing factors.

Introduction to Operations Management

Competitiveness

Product and Service Design

RELIABILITY – Static

Strategic Capacity Planning for Products and Services

Decision Theory– Static

Process Selection and Facility Layout

Work Design and Measurement

learning curve– Static

Location Planning and Analysis

The Transportation Model– Static

Management of Quality

Quality Control

Acceptance Sampling– Static

Aggregate Planning and Master Scheduling

MRP and ERP

Inventory Management

JIT and Lean Operations

Maintenance– Static

Supply Chain Management

Scheduling

Project Management

Management of Waiting Lines

Linear Programming

Filters