Question 1

________ is a time-series forecasting method that fits a trend line to a series of historical data points and then projects the line into the future for forecasts.

Accepted Answer

The answer of ________ is a time-series forecasting method that...

Question 2

A firm has modeled its experience with industrial accidents and found that the number of accidents per year (y-hat) is related to the number of employees (x) by the regression equation: y-hat = 3.3 + 0.049x. The r-squared value is 0.68. The regression is based on 20 annual observations. The firm intends to employ 480 workers next year. How many accidents do you project? How much confidence do you have in that forecast?

Accepted Answer

y-hat = 3.3 + 0.049(480) = 3.3 + 23.52 =

Question 3

________ expresses the error as a percent of the actual values.

Accepted Answer

A)  MAD 
B)  MSE 
C)  MAPE 
D)  FIT 
E)  The smoothing constant 
A)  MAD 
B)  MSE 
C)  MAPE 
D)  FIT 
E)  The smoothing constant

Question 4

Demand for a certain product is forecast to be 800 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 0.8. What is the seasonally-adjusted sales forecast for January?

Accepted Answer

A)  640 units 
B)  798.75 units 
C)  801.25 units 
D)  1000 units 
E)  83.33 units 
A)  640 units 
B)  798.75 units 
C)  801.25 units 
D)  1000 units 
E)  83.33 units

Question 5

Demand for a certain product is forecast to be 8,000 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January?

Accepted Answer

8,000 × 1.

Question 6

Forecasts used for new product planning, capital expenditures, facility location or expansion, and R&D typically utilize a:

Accepted Answer

A)  short-range time horizon. 
B)  medium-range time horizon. 
C)  long-range time horizon. 
D)  naive method, because there is no data history. 
E)  trend extrapolation. 
A)  short-range time horizon. 
B)  medium-range time horizon. 
C)  long-range time horizon. 
D)  naive method, because there is no data history. 
E)  trend extrapolation.

Question 7

Computer monitoring of tracking signals and self-adjustment if a signal passes a preset limit is characteristic of:

Accepted Answer

A)  exponential smoothing including trend. 
B)  adaptive smoothing. 
C)  trend projection. 
D)  focus forecasting. 
E)  multiple regression analysis. 
A)  exponential smoothing including trend. 
B)  adaptive smoothing. 
C)  trend projection. 
D)  focus forecasting. 
E)  multiple regression analysis.

Question 8

A naive forecast for September sales of a product would be equal to the sales in August.

Accepted Answer

A) True 
 B)False

Question 9

What is a time-series forecasting model?

Accepted Answer

A time-series foreca

Question 10

The forecasting technique that pools the opinions of a group of experts or managers is known as:

Accepted Answer

A)  the expert judgment model. 
B)  multiple regression. 
C)  jury of executive opinion. 
D)  market survey. 
E)  management coefficients. 
A)  the expert judgment model. 
B)  multiple regression. 
C)  jury of executive opinion. 
D)  market survey. 
E)  management coefficients.

Question 11

Which time-series model uses BOTH past forecasts and past demand data to generate a new forecast?

Accepted Answer

A)  naive 
B)  moving average 
C)  weighted moving average 
D)  exponential smoothing 
E)  trend projection 
A)  naive 
B)  moving average 
C)  weighted moving average 
D)  exponential smoothing 
E)  trend projection

Question 12

Which of the following statements about time-series forecasting is TRUE?

Accepted Answer

A)  It is always based on the assumption that future demand will be the same as past demand. 
B)  It makes extensive use of the data collected in the qualitative approach. 
C)  It is based on the assumption that the analysis of past demand helps predict future demand. 
D)  Because it accounts for trends, cycles, and seasonal patterns, it is always more powerful than associative forecasting. 
E)  All of these are true. 
A)  It is always based on the assumption that future demand will be the same as past demand. 
B)  It makes extensive use of the data collected in the qualitative approach. 
C)  It is based on the assumption that the analysis of past demand helps predict future demand. 
D)  Because it accounts for trends, cycles, and seasonal patterns, it is always more powerful than associative forecasting. 
E)  All of these are true.

Question 13

________ is a forecasting technique based upon salespersons' estimates of expected sales.

Accepted Answer

Sales forc

Question 14

Jim's department at a local department store has tracked the sales of a product over the last ten weeks. Forecast demand using exponential smoothing with an alpha of 0.3, and an initial forecast of 30.0 for period 1. Calculate the MAD covering periods 2-10. Calculate the tracking signal covering periods 2-10. What do you recommend?

Accepted Answer

@#IMG-DLM& The tracking signal RSFE/MAD

Question 15

A forecasting method has produced the following over the past five months. What is the mean absolute deviation?

Accepted Answer

A)  -0.2 
B)  12.0 
C)  6.0 
D)  1.2 
E)  2.4 
A)  -0.2 
B)  12.0 
C)  6.0 
D)  1.2 
E)  2.4

Question 16

A seasonal index for a monthly series is about to be calculated on the basis of three years' accumulation of data. The three previous July values were 110, 135, and 130. The average over all months is 110. What is the approximate seasonal index for July?

Accepted Answer

(110 + 135

Question 17

Many services maintain records of sales noting:

Accepted Answer

A)  the day of the week. 
B)  unusual events. 
C)  the weather. 
D)  holiday impacts. 
E)  all of these. 
A)  the day of the week. 
B)  unusual events. 
C)  the weather. 
D)  holiday impacts. 
E)  all of these.

Question 18

A naive forecast for September sales of a product would be equal to the forecast for August.

Accepted Answer

A) True 
 B)False

Question 19

A small family-owned restaurant uses a seven-day moving average model to determine manpower requirements. These forecasts need to be seasonalized because each day of the week has its own demand pattern. The seasonal indices for each day of the week are: Monday 0.445; Tuesday 0.791; Wednesday 0.927; Thursday 1.033; Friday 1.422; Saturday 1.478; and Sunday 0.903. Average daily demand based on the most recent moving average is 194 patrons. What is the seasonalized forecast for each day of next week?

Accepted Answer

The average value multiplied by each day

Question 20

________ forecasts are concerned with rates of technological progress, which can result in the birth of exciting new products, requiring new plants and equipment.

Accepted Answer

The answer of ________ forecasts are concerned with rates of...

________ is a time-series forecasting method that fits a trend line to a series of historical data points and then projects the line into the future for forecasts.

________ expresses the error as a percent of the actual values.

Demand for a certain product is forecast to be 800 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 0.8. What is the seasonally-adjusted sales forecast for January?

Demand for a certain product is forecast to be 8,000 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January?

Forecasts used for new product planning, capital expenditures, facility location or expansion, and R&D typically utilize a:

Computer monitoring of tracking signals and self-adjustment if a signal passes a preset limit is characteristic of:

A naive forecast for September sales of a product would be equal to the sales in August.

What is a time-series forecasting model?

The forecasting technique that pools the opinions of a group of experts or managers is known as:

Which time-series model uses BOTH past forecasts and past demand data to generate a new forecast?

Which of the following statements about time-series forecasting is TRUE?

________ is a forecasting technique based upon salespersons' estimates of expected sales.

A forecasting method has produced the following over the past five months. What is the mean absolute deviation?

A seasonal index for a monthly series is about to be calculated on the basis of three years' accumulation of data. The three previous July values were 110, 135, and 130. The average over all months is 110. What is the approximate seasonal index for July?

Many services maintain records of sales noting:

A naive forecast for September sales of a product would be equal to the forecast for August.

________ forecasts are concerned with rates of technological progress, which can result in the birth of exciting new products, requiring new plants and equipment.

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Exam 4: Forecasting

________ is a time-series forecasting method that fits a trend line to a series of historical data points and then projects the line into the future for forecasts.

________ expresses the error as a percent of the actual values.

Demand for a certain product is forecast to be 800 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 0.8. What is the seasonally-adjusted sales forecast for January?

Demand for a certain product is forecast to be 8,000 units per month, averaged over all 12 months of the year. The product follows a seasonal pattern, for which the January monthly index is 1.25. What is the seasonally-adjusted sales forecast for January?

Forecasts used for new product planning, capital expenditures, facility location or expansion, and R&D typically utilize a:

Computer monitoring of tracking signals and self-adjustment if a signal passes a preset limit is characteristic of:

A naive forecast for September sales of a product would be equal to the sales in August.

What is a time-series forecasting model?

The forecasting technique that pools the opinions of a group of experts or managers is known as:

Which time-series model uses BOTH past forecasts and past demand data to generate a new forecast?

Which of the following statements about time-series forecasting is TRUE?

________ is a forecasting technique based upon salespersons' estimates of expected sales.

A forecasting method has produced the following over the past five months. What is the mean absolute deviation?

A seasonal index for a monthly series is about to be calculated on the basis of three years' accumulation of data. The three previous July values were 110, 135, and 130. The average over all months is 110. What is the approximate seasonal index for July?

Many services maintain records of sales noting:

A naive forecast for September sales of a product would be equal to the forecast for August.

________ forecasts are concerned with rates of technological progress, which can result in the birth of exciting new products, requiring new plants and equipment.

Operations and Productivity

Operations Strategy in a Global Environment

Project Management

Design of Goods and Services

Managing Quality

Process Strategies

Location Strategies

Human Resources, Job Design, and Work Measurement

Supply Chain Management

Inventory Management

Aggregate Planning and Sop

Material Requirements Planning Mrp and Erp

Short-Term Scheduling

Lean Operations

Maintenance and Reliability

Decision-Making Tools

Linear Programming

Transportation Models

Waiting-Line Models

Learning Curves

Simulation

Applying Analytics to Big Data in Operations Management

Filters