Question 1

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

Accepted Answer

A) 0 
B) 1 divided by the number of periods 
C) 0.5 
D) 1.0 
E) cannot be determined 
A) 0 
B) 1 divided by the number of periods 
C) 0.5 
D) 1.0 
E) cannot be determined

Question 2

The larger the standard error of the estimate,the more accurate the forecasting model.

Accepted Answer

A) True 
 B)False

Question 3

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 the above 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 the above are true.

Question 4

A fundamental distinction between trend projection and linear regression is that:

Accepted Answer

A) trend projection uses least squares while linear regression does not. 
B) only linear regression can have a negative slope. 
C) in trend projection the independent variable is time; in linear regression the independent variable need not be time,but can be any variable with explanatory power. 
D) trend projection can be a function of several variables,while linear regression can only be a function of one variable. 
E) trend projection uses two smoothing constants,not just one. 
A) trend projection uses least squares while linear regression does not. 
B) only linear regression can have a negative slope. 
C) in trend projection the independent variable is time; in linear regression the independent variable need not be time,but can be any variable with explanatory power. 
D) trend projection can be a function of several variables,while linear regression can only be a function of one variable. 
E) trend projection uses two smoothing constants,not just one.

Question 5

What is the difference between an associative model and a time-series model?

Accepted Answer

A time-series model uses only historical

Question 6

Forecasts of individual products tend to be more accurate than forecasts of product families.

Accepted Answer

A) True 
 B)False

Question 7

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 8

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 160.What is the approximate seasonal index for July?

Accepted Answer

(110 + 135

Question 9

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 10

Focus forecasting tries a variety of computer models and selects the best one for a particular application.

Accepted Answer

A) True 
 B)False

Question 11

John's House of Pancakes uses a weighted moving average method to forecast pancake sales.It assigns a weight of 5 to the previous month's demand,3 to demand two months ago,and 1 to demand three months ago.If sales amounted to 1000 pancakes in May,2200 pancakes in June,and 3000 pancakes in July,what should be the forecast for August?

Accepted Answer

A) 2400 
B) 2511 
C) 2067 
D) 3767 
E) 1622 
A) 2400 
B) 2511 
C) 2067 
D) 3767 
E) 1622

Question 12

Seasonal indices adjust raw data for patterns that repeat at regular time intervals.

Accepted Answer

A) True 
 B)False

Question 13

Weekly sales of ten-grain bread at the local organic food market are provided in the table below.Based on these data,forecast week 9 using a five-week moving average.

Accepted Answer

(382 + 410

Question 14

________ 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 15

What is the forecast for May using a four-month moving average?

Accepted Answer

A) 38 
B) 42 
C) 43 
D) 44 
E) 47 
A) 38 
B) 42 
C) 43 
D) 44 
E) 47

Question 16

Identify the seven steps involved in forecasting.

Accepted Answer

1.Determine the use of the forecast. 2.S

Question 17

Which time-series model below assumes that demand in the next period will be equal to the most recent period's demand?

Accepted Answer

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

Question 18

What is the key difference between weighted moving average and simple moving average approaches to forecasting?

Accepted Answer

Simple moving averages are useful where

Question 19

The last four weekly values of sales were 80,100,105,and 90 units,respectively.The last four forecasts (for the same four weeks)were 60,80,95,and 75 units,respectively.Calculate the MAD,MSE,and MAPE for these four weeks.

Accepted Answer

MAD = 65/4 = 16.25;

Question 20

What forecasting systems combine the intelligence of multiple supply chain partners?

Accepted Answer

A) FORE 
B) MULTISUP 
C) CPFR 
D) SUPPLY 
E) MSCP 
A) FORE 
B) MULTISUP 
C) CPFR 
D) SUPPLY 
E) MSCP

Exam 4: Forecasting

Which of the following smoothing constants would make an exponential smoothing forecast equivalent to a naive forecast?

The larger the standard error of the estimate,the more accurate the forecasting model.

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

A fundamental distinction between trend projection and linear regression is that:

What is the difference between an associative model and a time-series model?

Forecasts of individual products tend to be more accurate than forecasts of product families.

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 160.What is the approximate seasonal index for July?

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

Focus forecasting tries a variety of computer models and selects the best one for a particular application.

Seasonal indices adjust raw data for patterns that repeat at regular time intervals.

Weekly sales of ten-grain bread at the local organic food market are provided in the table below.Based on these data,forecast week 9 using a five-week moving average.

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

What is the forecast for May using a four-month moving average?

Identify the seven steps involved in forecasting.

Which time-series model below assumes that demand in the next period will be equal to the most recent period's demand?

What is the key difference between weighted moving average and simple moving average approaches to forecasting?

The last four weekly values of sales were 80,100,105,and 90 units,respectively.The last four forecasts (for the same four weeks)were 60,80,95,and 75 units,respectively.Calculate the MAD,MSE,and MAPE for these four weeks.

What forecasting systems combine the intelligence of multiple supply chain partners?

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