Forecast that reflect very little happenstance fluctuation in the

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Question 1

  1. Forecast that reflect very little happenstance fluctuation in the past data are said to exhibit

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1.

Seasonal effects

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2.

noise dampening response

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3.

impulse response

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4.

all of the above

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5.

none of the above

5 points  

Question 2

  1. A Winter’s forecasting model that has zero values for the beta and gamma constants exhibit what type of behavior

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1.

A simple exponential smoothing model

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2.

Impulse response

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3.

Noise dampening

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4.

all of the above

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5.

none of the above

5 points  

Question 3

  1. In measuring forecast accuracy, the average of the absolute difference between the forecast and the actual demand is called

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1.

alpha

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2.

E-bar

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3.

MAD

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4.

all of the above

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5.

none of the above

5 points  

Question 4

  1. Choice the best type of forecasting methods for the type of data indicated
 

trend data that fits in a straight line

 

   

 

       

 

 

short range forecast with no trends or seasonal effects

   

 

 

random data with no seasonal effects or trends

   

 

 

random data that illustrates a trend or seasonal pattern

   
  1.  
  2.  
 

random data with a trend or no seasonal effect

A.

Exponential Smoothing

B.

Winter’s Method

C.

Holt’s Method

D.

Linear Regression

E.

Moving Average

20 points  

Question 5

  1. In order to establish a forecast method that exhibits impulse response;

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1.

an exponential smoothing forecast method should be used

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2.

the data must be linear

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3.

The alpha coefficient should be set close to 1 for exponential smoothing

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4.

The alpha coefficient should be set close to 0 for exponential smoothing

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5.

None of the above

5 points  

Question 6

  1. Refer to the data in table 1 posted in the discussion folder. Using the data, what is the forecast for November if a three month moving average model is used?

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1.

49.25

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2.

50.67

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3.

53.00

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4.

none of the above

5 points  

Question 7

  1. Refer to the data in table 1 posted in the discussion folder. Using the data, which month has a demand forecast equal to 55 for a 3 month moving average approach

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1.

April

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2.

June

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3.

August

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4.

October

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5.

None of the above

5 points  

Question 8

  1. Refer to the data in table 1 posted in the discussion folder. Using the data, what is the November forecast if exponential smoothing is used with an alpha value = .1

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1.

47.9

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2.

53.2

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3.

40.8

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4.

51.6

5 points  

Question 9

  1. Refer to the data, table 1, from the discussion folder. Using this data, what is the forecast error % for an exponential smoothing model with a alpha of .6

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1.

10%

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2.

12%

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3.

14%

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4.

16%

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5.

18%

5 points  

Question 10

  1. Forecasting models are an integral part of business planning that requies input from

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1.

marketing

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2.

demand estimates

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3.

sales forecast

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4.

all of the above

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5.

none of the above

5 points  

Question 11

  1. The alpha coefficient in exponential smothing

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1.

is set equal to the actual value in period 1

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2.

varies over a time series of data

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3.

is a value between 0 and 1

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4.

all of the above

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5.

none of the above

5 points  

Question 12

  1. Quarterly data which reflect an increase every fourth quarter followed by a decrease every first quarter are said to be

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1.

seasonal

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2.

cyclical

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3.

periodical

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4.

abnormal

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5.

following a trend

5 points  

Question 13

  1. To deseasonalize time series data

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1.

divide each actual value by the trend line intercept

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2.

divide each actual value by its seasonal index factor

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3.

divide each actual value by total forecast error

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4.

divide each actual value by the alpha coefficient

5 points  

Question 14

  1. A linear trend for 12 months of data is y = 339.02 + 23.96x. What is the forecast for the next quarter (January, Feruary and March)?

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1.

1160.82

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2.

1807.74

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3.

2023.38

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4.

3641.59

5 points  

Question 15

  1. Refer to the data in table 1 posted in the discussion folder. Using the data, what is the MAD for an exponential smoothing model with alpha = .1

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1.

6.2

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2.

7.7

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3.

8.3

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4.

8.8

5 points  

Question 16

  1. The delphi method of forecasting is

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1.

time series method for detecting seasonality

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2.

variation of exponential smoothing method

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3.

multiple regression method

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4.

qualitative method which solicits from experts

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5.

qualitative method for researching similar to data

5 points  

Question 17

  1. The ideal value of MAD is

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1.

0

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2.

100

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3.

10

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4.

none of the above

5 points  

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