The following table contains the demand from the last 10 months: MONTH ACTUAL DEMAND 31 34 a. Calculate the single exponential smoothing forecast for these data using an or of 30 and an initial forecast (Fg of 31. (Round your answers to 2 decimal places) Month 4 5 6 7 . 9 3 4 51 6. Calculate the exponential smoothing with trend forecast for these data using and of 0.30, a 6 of 0.30, an initial trend forecast (7 of 1, and an initial exponentially smoothed forecast (Fg of 30. (Round your answers to 2 decimal places) @ Exponential Smoothing 10 35 37 36 38 40 40 41 FIT et Calculate the mean absolute deviation (MAD) for the last nine months of forecasts (Round your answers to 2 decimal places) MAD Single exponendal smoothing foreca Exponential anothing with trend forecast e-2. Which is best? Single exponential smoothing forecast Exponential smoothing with send forecast
The following table contains the demand from the last 10 months: MONTH ACTUAL DEMAND 31 34 a. Calculate the single exponential smoothing forecast for these data using an or of 30 and an initial forecast (Fg of 31. (Round your answers to 2 decimal places) Month 4 5 6 7 . 9 3 4 51 6. Calculate the exponential smoothing with trend forecast for these data using and of 0.30, a 6 of 0.30, an initial trend forecast (7 of 1, and an initial exponentially smoothed forecast (Fg of 30. (Round your answers to 2 decimal places) @ Exponential Smoothing 10 35 37 36 38 40 40 41 FIT et Calculate the mean absolute deviation (MAD) for the last nine months of forecasts (Round your answers to 2 decimal places) MAD Single exponendal smoothing foreca Exponential anothing with trend forecast e-2. Which is best? Single exponential smoothing forecast Exponential smoothing with send forecast
Practical Management Science
6th Edition
ISBN:9781337406659
Author:WINSTON, Wayne L.
Publisher:WINSTON, Wayne L.
Chapter2: Introduction To Spreadsheet Modeling
Section: Chapter Questions
Problem 20P: Julie James is opening a lemonade stand. She believes the fixed cost per week of running the stand...
Related questions
Question
![The following table contains the demand from the last 10 months:
MONTH ACTUAL DEMAND
1
2
6
7
10
3
4
5
6
7
8
9
a. Calculate the single exponential smoothing forecast for these data using an a of 30 and an initial forecast (F of 31. (Round your
answers to 2 decimal places)
Month
50
Month
31
4
5
6
7
b. Calculate the exponential smoothing with trend forecast for these data using and of 0:30, a 5 of 0.30, an initial trend forecast (Tof
1, and an initial exponentially smoothed forecast (F3 of 30. (Round your answers to 2 decimal places)
B
9
Exponential
Smoothing
10
31
34
33
35
FITI
37
36
38
40
40
41
e-2. Which is best?
c-1. Calculate the mean absolute deviation (MAD) for the last nine months of forecasts (Round your answers to 2 decimal places)
MAD
Single exponential smoothing forecast
Exponential amoothing with trend forecast
Single exponential smoothing forecast
O Exponential smoothing with trend forecast](/v2/_next/image?url=https%3A%2F%2Fcontent.bartleby.com%2Fqna-images%2Fquestion%2F1dafe049-f9b9-4486-be95-08611377b4e6%2Fc2ce0208-0be6-4562-ab0a-242c1b325ab1%2Fe0lszdl_processed.jpeg&w=3840&q=75)
Transcribed Image Text:The following table contains the demand from the last 10 months:
MONTH ACTUAL DEMAND
1
2
6
7
10
3
4
5
6
7
8
9
a. Calculate the single exponential smoothing forecast for these data using an a of 30 and an initial forecast (F of 31. (Round your
answers to 2 decimal places)
Month
50
Month
31
4
5
6
7
b. Calculate the exponential smoothing with trend forecast for these data using and of 0:30, a 5 of 0.30, an initial trend forecast (Tof
1, and an initial exponentially smoothed forecast (F3 of 30. (Round your answers to 2 decimal places)
B
9
Exponential
Smoothing
10
31
34
33
35
FITI
37
36
38
40
40
41
e-2. Which is best?
c-1. Calculate the mean absolute deviation (MAD) for the last nine months of forecasts (Round your answers to 2 decimal places)
MAD
Single exponential smoothing forecast
Exponential amoothing with trend forecast
Single exponential smoothing forecast
O Exponential smoothing with trend forecast
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