Consider the following data:
Month | Jan-14 | Feb-14 | Mar-14 | Apr-14 | May-14 | Jun-14 | Jul-14 | Aug-14 | Sep-14 |
---|---|---|---|---|---|---|---|---|---|
Profit ($) | 16,416 |
16,566 |
15,355 |
17,420 |
19,063 |
17,240 |
19,138 |
18,501 |
20,290 |
Step 3 of 4 :
Determine the exponential smoothing forecast for the next time period using a smoothing constant of 0.30
. If necessary, round your answer to one decimal place.
actual | forecast | |
Jan-14 | 16416 | |
Feb-14 | 16566 | 16416.000 |
Mar-14 | 15355 | 16461.000 |
Apr-14 | 17420 | 16129.200 |
May-14 | 19063 | 16516.440 |
Jun-14 | 17240 | 17280.408 |
Jul-14 | 19138 | 17268.286 |
Aug-14 | 18501 | 17829.200 |
Sep-14 | 20290 | 18030.740 |
Oct-14 | 18708.518 |
from above exponential smoothing forecast for the next time period =18708.5
Consider the following data: Monthly Profit of an Auto Repair Shop Month Jan-14 Feb-14 Mar-14 Apr-14...
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