Question 1

New forecast = [(α *latest observation)+((1 - α)* old forecast)] is the formula for ______.

Accepted Answer

A) moving average 
B) weighted moving average 
C) exponential smoothing 
D) factor rating method 
A) moving average 
B) weighted moving average 
C) exponential smoothing 
D) factor rating method C

Question 2

Which of the following statements is true about the coefficient of determination (R²)?

Accepted Answer

A) The higher the value of R²,the more confidence we have that the estimate is accurate. 
B) The lower the value of R²,the more confidence we have that the estimate is accurate. 
C) The value of R² has no significance on the accuracy of the estimate. 
D) The estimate is accurate when R² = 0. 
A) The higher the value of R²,the more confidence we have that the estimate is accurate. 
B) The lower the value of R²,the more confidence we have that the estimate is accurate. 
C) The value of R² has no significance on the accuracy of the estimate. 
D) The estimate is accurate when R² = 0. A

Question 3

The use of ______ involves establishing an upper and lower control limit to determine if the forecasting errors related to a method are within the limits.

Accepted Answer

A) tracking signals 
B) control charts 
C) monitoring signals 
D) trend charts 
A) tracking signals 
B) control charts 
C) monitoring signals 
D) trend charts A

Question 4

Product scheduling and worker assignments are examples of forecasted activities in ______ decision-making.

Accepted Answer

A) operational 
B) tactical 
C) strategic 
D) functional 
A) operational 
B) tactical 
C) strategic 
D) functional

Question 5

Which of the following is NOT a major component of a time series?

Accepted Answer

A) seasonal variations 
B) trend line 
C) irregular variations 
D) best-fit line 
A) seasonal variations 
B) trend line 
C) irregular variations 
D) best-fit line

Question 6

The independent variable in linear regression analysis is also referred to as the ______.

Accepted Answer

A) predicted variable 
B) predictor variable 
C) random variable 
D) discrete variable 
A) predicted variable 
B) predictor variable 
C) random variable 
D) discrete variable

Question 7

Simple exponential smoothing or the first-order smoothing model can be used when ______.

Accepted Answer

A) demand exhibits different types of trend patterns 
B) demand is constant or level 
C) demand exhibits both trend and seasonal patterns 
D) demand is fluctuating 
A) demand exhibits different types of trend patterns 
B) demand is constant or level 
C) demand exhibits both trend and seasonal patterns 
D) demand is fluctuating

Question 8

Which of the following statements is false about trend patterns?

Accepted Answer

A) Trend is the long-term movement of data over time. 
B) Damped trend occurs when the level of demand increases initially,but over the long run,it levels off. 
C) Exponential decline occurs when each succeeding observation decreases by some constant factor. 
D) Linear trend often occurs when new products are introduced. 
A) Trend is the long-term movement of data over time. 
B) Damped trend occurs when the level of demand increases initially,but over the long run,it levels off. 
C) Exponential decline occurs when each succeeding observation decreases by some constant factor. 
D) Linear trend often occurs when new products are introduced.

Question 9

______ is a predictive technique that models the relationship between a dependent variable and one or more independent variables.

Accepted Answer

A) Linear regression analysis 
B) Linear trend multiplicative method 
C) Linear trend additive method 
D) Second-order or double smoothing 
A) Linear regression analysis 
B) Linear trend multiplicative method 
C) Linear trend additive method 
D) Second-order or double smoothing

Question 10

Which of the following models can be used when demand exhibits both trend and seasonal patterns?

Accepted Answer

A) simple exponential smoothing 
B) second-order or double smoothing 
C) third-order or triple smoothing 
D) complex exponential smoothing 
A) simple exponential smoothing 
B) second-order or double smoothing 
C) third-order or triple smoothing 
D) complex exponential smoothing

Question 11

Which of the following is NOT a way to measure forecasting errors?

Accepted Answer

A) mean squared error (MS
E)  
B) mean absolute deviation (MA
D)  
C) mean absolute percentage error (MAP
E)  
D) error sum of squares (SS
E)  
A) mean squared error (MS
E)  
B) mean absolute deviation (MA
D)  
C) mean absolute percentage error (MAP
E)  
D) error sum of squares (SS
E)

Question 12

Which of the following is NOT a measure of variation that must be calculated prior to determining the value of coefficient of determination (R²)?

Accepted Answer

A) total sum of squares (SST) 
B) error sum of squares (SS
E)  
C) regression sum of squares (SSR) 
D) cumulative sum of error (CS
E)  
A) total sum of squares (SST) 
B) error sum of squares (SS
E)  
C) regression sum of squares (SSR) 
D) cumulative sum of error (CS
E)

Question 13

The coefficient of determination has a value between ______.

Accepted Answer

A) 0 and 1 
B) -1 and +1 
C) -∞ to +∞ 
D) -1 to 0 
A) 0 and 1 
B) -1 and +1 
C) -∞ to +∞ 
D) -1 to 0

Question 14

Which of the following is NOT an example of short-term time series forecasting methods?

Accepted Answer

A) naïve approach 
B) moving averages 
C) exponential smoothing 
D) expert opinion 
A) naïve approach 
B) moving averages 
C) exponential smoothing 
D) expert opinion

Question 15

Exponential growth/decline are examples of ______.

Accepted Answer

A) seasonal trend 
B) linear trend 
C) nonlinear trend 
D) damped trend 
A) seasonal trend 
B) linear trend 
C) nonlinear trend 
D) damped trend

Question 16

Which of the following statements is true about quantitative methods?

Accepted Answer

A) They are appropriate for demand forecasting if there are causal relationships between explanatory variables. 
B) They cannot be used for short or medium-to-intermediate timeframes. 
C) They are used if measurable,historical data are not available. 
D) They are inappropriate for demand forecasting if there are causal relationships between explanatory variables. 
A) They are appropriate for demand forecasting if there are causal relationships between explanatory variables. 
B) They cannot be used for short or medium-to-intermediate timeframes. 
C) They are used if measurable,historical data are not available. 
D) They are inappropriate for demand forecasting if there are causal relationships between explanatory variables.

Question 17

______ is a short-term time series forecasting method in which forecasters assign more weight to most recent values in the time series if they feel that these values reflect how the actual demand will behave in the near future.

Accepted Answer

A) Moving average 
B) Linear trend multiplicative method 
C) Weighted moving average 
D) Linear regression technique 
A) Moving average 
B) Linear trend multiplicative method 
C) Weighted moving average 
D) Linear regression technique

Question 18

______ variations are treated as outliers and are eliminated from consideration for forecasting purposes.

Accepted Answer

A) Cyclical 
B) Seasonal 
C) Irregular 
D) Regular 
A) Cyclical 
B) Seasonal 
C) Irregular 
D) Regular

Question 19

Increased retail sales in December and peak demand for snow shovels during winter are examples of ______

Accepted Answer

A) cyclical variations 
B) seasonal variations 
C) irregular variations 
D) random variations 
A) cyclical variations 
B) seasonal variations 
C) irregular variations 
D) random variations

Question 20

______ method results in a straight line that minimizes the sum of the squares of the differences between the line and each of the actual observations.

Accepted Answer

A) Best-fit 
B) Straight-line 
C) Least-squares 
D) Linear-line 
A) Best-fit 
B) Straight-line 
C) Least-squares 
D) Linear-line

Exam 16: Demand Forecasting Methods

New forecast = [(α *latest observation)+((1 - α)* old forecast)] is the formula for ______.

Which of the following statements is true about the coefficient of determination (R²)?

The use of ______ involves establishing an upper and lower control limit to determine if the forecasting errors related to a method are within the limits.

Product scheduling and worker assignments are examples of forecasted activities in ______ decision-making.

Which of the following is NOT a major component of a time series?

The independent variable in linear regression analysis is also referred to as the ______.

Simple exponential smoothing or the first-order smoothing model can be used when ______.

Which of the following statements is false about trend patterns?

______ is a predictive technique that models the relationship between a dependent variable and one or more independent variables.

Which of the following models can be used when demand exhibits both trend and seasonal patterns?

Which of the following is NOT a way to measure forecasting errors?

Which of the following is NOT a measure of variation that must be calculated prior to determining the value of coefficient of determination (R²)?

The coefficient of determination has a value between ______.

Which of the following is NOT an example of short-term time series forecasting methods?

Exponential growth/decline are examples of ______.

Which of the following statements is true about quantitative methods?

______ is a short-term time series forecasting method in which forecasters assign more weight to most recent values in the time series if they feel that these values reflect how the actual demand will behave in the near future.

______ variations are treated as outliers and are eliminated from consideration for forecasting purposes.

Increased retail sales in December and peak demand for snow shovels during winter are examples of ______

______ method results in a straight line that minimizes the sum of the squares of the differences between the line and each of the actual observations.

Introduction to Managing Global Operations and Supply Chains

Operations and Supply Chain Strategies

Project Management

Supplement: Project Management

Product and Service Innovations

Supplement: Reliability

Managing for Quality

Quality Improvement and Control Tools

Capacity Planning

Supply Chain Design and Location Planning

Process Design and Layout Planning

Supplement: Tools for Analyzing, Designing, and Selecting Processes and Layouts

Supplier Management

Logistics Management

Demand Management and Customer Service

Lean Operations and Supply Chains

Inventory Management

Inventory Control Models

Sales and Operations Planning

Master Scheduling and Material Requirements Planning

Supplement: Capacity Requirements Planning, MRP II, ERP, and DRP

Detailed Scheduling

Linear Programming

The Transportation Models

Waiting Line Models

Simulation

Learning Curves

Decision-Making Tools

Filters

New forecast = [(α latest observation)+((1 - α) old forecast)] is the formula for ______.