Forecast that reflect very little happenstance fluctuation in the

Question 1

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

[removed]

1.

Seasonal effects

[removed]

2.

noise dampening response

[removed]

3.

impulse response

[removed]

4.

all of the above

[removed]

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

[removed]

1.

A simple exponential smoothing model

[removed]

2.

Impulse response

[removed]

3.

Noise dampening

[removed]

4.

all of the above

[removed]

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

[removed]

1.

alpha

[removed]

2.

E-bar

[removed]

3.

MAD

[removed]

4.

all of the above

[removed]

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;

[removed]

1.

an exponential smoothing forecast method should be used

[removed]

2.

the data must be linear

[removed]

3.

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

[removed]

4.

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

[removed]

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?

[removed]

1.

49.25

[removed]

2.

50.67

[removed]

3.

53.00

[removed]

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

[removed]

1.

April

[removed]

2.

June

[removed]

3.

August

[removed]

4.

October

[removed]

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

[removed]

1.

47.9

[removed]

2.

53.2

[removed]

3.

40.8

[removed]

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

[removed]

1.

10%

[removed]

2.

12%

[removed]

3.

14%

[removed]

4.

16%

[removed]

5.

18%

5 points  

Question 10

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

[removed]

1.

marketing

[removed]

2.

demand estimates

[removed]

3.

sales forecast

[removed]

4.

all of the above

[removed]

5.

none of the above

5 points  

Question 11

  1. The alpha coefficient in exponential smothing

[removed]

1.

is set equal to the actual value in period 1

[removed]

2.

varies over a time series of data

[removed]

3.

is a value between 0 and 1

[removed]

4.

all of the above

[removed]

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

[removed]

1.

seasonal

[removed]

2.

cyclical

[removed]

3.

periodical

[removed]

4.

abnormal

[removed]

5.

following a trend

5 points  

Question 13

  1. To deseasonalize time series data

[removed]

1.

divide each actual value by the trend line intercept

[removed]

2.

divide each actual value by its seasonal index factor

[removed]

3.

divide each actual value by total forecast error

[removed]

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)?

[removed]

1.

1160.82

[removed]

2.

1807.74

[removed]

3.

2023.38

[removed]

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

[removed]

1.

6.2

[removed]

2.

7.7

[removed]

3.

8.3

[removed]

4.

8.8

5 points  

Question 16

  1. The delphi method of forecasting is

[removed]

1.

time series method for detecting seasonality

[removed]

2.

variation of exponential smoothing method

[removed]

3.

multiple regression method

[removed]

4.

qualitative method which solicits from experts

[removed]

5.

qualitative method for researching similar to data

5 points  

Question 17

  1. The ideal value of MAD is

[removed]

1.

0

[removed]

2.

100

[removed]

3.

10

[removed]

4.

none of the above

5 points  

Click Save and Submit to save and submit. Click Save All Answers to save all answers.

 

Place your order
(550 words)

Approximate price: $22

Calculate the price of your order

550 words
We'll send you the first draft for approval by September 11, 2018 at 10:52 AM
Total price:
$26
The price is based on these factors:
Academic level
Number of pages
Urgency
Basic features
  • Free title page and bibliography
  • Unlimited revisions
  • Plagiarism-free guarantee
  • Money-back guarantee
  • 24/7 support
On-demand options
  • Writer’s samples
  • Part-by-part delivery
  • Overnight delivery
  • Copies of used sources
  • Expert Proofreading
Paper format
  • 275 words per page
  • 12 pt Arial/Times New Roman
  • Double line spacing
  • Any citation style (APA, MLA, Chicago/Turabian, Harvard)

Our guarantees

Delivering a high-quality product at a reasonable price is not enough anymore.
That’s why we have developed 5 beneficial guarantees that will make your experience with our service enjoyable, easy, and safe.

Money-back guarantee

You have to be 100% sure of the quality of your product to give a money-back guarantee. This describes us perfectly. Make sure that this guarantee is totally transparent.

Read more

Zero-plagiarism guarantee

Each paper is composed from scratch, according to your instructions. It is then checked by our plagiarism-detection software. There is no gap where plagiarism could squeeze in.

Read more

Free-revision policy

Thanks to our free revisions, there is no way for you to be unsatisfied. We will work on your paper until you are completely happy with the result.

Read more

Privacy policy

Your email is safe, as we store it according to international data protection rules. Your bank details are secure, as we use only reliable payment systems.

Read more

Fair-cooperation guarantee

By sending us your money, you buy the service we provide. Check out our terms and conditions if you prefer business talks to be laid out in official language.

Read more