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 naive approach?

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

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

A) 0 B) 200 C) 400 D) 180 E) 360 A) 0 B) 200 C) 400 D) 180 E) 360

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

A) 2,600 B) 2,760 C) 2,800 D) 3,840 E) 3,000 A) 2,600 B) 2,760 C) 2,800 D) 3,840 E) 3,000

Exam 3: Forecasting

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 naive approach?

(Multiple Choice)

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Question 21

Which of the following features would not generally be considered common to all forecasts?

(Multiple Choice)

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Question 22

The best forecast is not necessarily the most accurate.

(True/False)

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Question 23

In order to compute seasonal relatives, the trend of past data must be computed or known, which means that for brand-new products this approach cannot be used.

(True/False)

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Question 24

The primary method for associative forecasting is:

(Multiple Choice)

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Question 25

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

(Multiple Choice)

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Question 26

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: Year Enrollment Four years ago 2000 Three years ago 2200 Two years ago 2800 Last year 3000 What is the annual rate of change (slope) of the least squares trend line for these data?

(Multiple Choice)

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Question 27

The sample standard deviation of forecast error is estimated by the square root of MSE.

(True/False)

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Question 28

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: What is this week's forecast using trend-adjusted (double) smoothing with alpha = .5 and beta = .1, if the forecast for last week was 65, the forecast for two weeks ago was 75, and the trend estimate for last week's forecast was -5?

(Multiple Choice)

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Question 29

Which of the following mechanisms for enhancing profitability is most likely to result from improving short-term forecast performance?

(Multiple Choice)

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Question 30

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.

(Multiple Choice)

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Question 31

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: Year Enrollment Four years ago 2000 Three years ago 2200 Two years ago 2800 Last year 3000 What is this year's forecast using exponential smoothing with alpha = .4, if last year's smoothed forecast was 2,600?

(Multiple Choice)

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Question 32

A tracking signal focuses on the ratio of cumulative forecast error to the corresponding value of MAD.

(True/False)

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Question 33

The two most important factors in choosing a forecasting technique are:

(Multiple Choice)

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Question 34

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:

(Multiple Choice)

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Question 35

Which of the following would be an advantage of using a sales force composite to develop a demand forecast?

(Multiple Choice)

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Question 36

A smoothing constant of .1 will cause an exponential smoothing forecast to react more quickly to a sudden change than a smoothing constant value of .3.

(True/False)

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Question 37

Which phrase most closely describes the Delphi technique?

(Multiple Choice)

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Question 38

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

(Multiple Choice)

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Question 39

Given forecast errors of 5, 0, -4, and 3, what is the tracking signal?

(Multiple Choice)

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Question 40

Showing 21 - 40 of 139

Exam 3: Forecasting

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 naive approach?

Which of the following features would not generally be considered common to all forecasts?

The best forecast is not necessarily the most accurate.

In order to compute seasonal relatives, the trend of past data must be computed or known, which means that for brand-new products this approach cannot be used.

The primary method for associative forecasting is:

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

The sample standard deviation of forecast error is estimated by the square root of MSE.

Which of the following mechanisms for enhancing profitability is most likely to result from improving short-term forecast performance?

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.

A tracking signal focuses on the ratio of cumulative forecast error to the corresponding value of MAD.

The two most important factors in choosing a forecasting technique are:

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:

Which of the following would be an advantage of using a sales force composite to develop a demand forecast?

A smoothing constant of .1 will cause an exponential smoothing forecast to react more quickly to a sudden change than a smoothing constant value of .3.

Which phrase most closely describes the Delphi technique?

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

Given forecast errors of 5, 0, -4, and 3, what is the tracking signal?

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

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.