| Month (X) | Sony Walkman Sales ($ in Mil), Y | SSE | A | ?? | Instructions: | Points | |||||||||
| 1 | 3.9 | ?? | B | ?? | 1) Review the Sales data (Y) for Sony Walkman after launch by month (X) (in cells A1 to B24) |
||||||||||
| 2 | 5.3 | C | ?? | ||||||||||||
| 3 | 7.2 | 2) Let’s assume you would like to Predict Y using a 2nd order polynomial equation as shown below. |
|||||||||||||
| 4 | 9.6 |
|
|||||||||||||
| 5 | 12 | ||||||||||||||
| 6 | 17 | ||||||||||||||
| 7 | 23 | 3) Optimize parametersA, B, and C,with non-linear forecasting techniques, such that SSE (Sum of Squared Errors) is Minimal |
|||||||||||||
| 8 | 31 | Enter the value of A in H1 (use 4 decimals, example: 1.2345) | |||||||||||||
| 9 | 38 | Enter the value of B in H2 (use 4 decimals, example: 1.2345) | |||||||||||||
| 10 | 50 | Enter the value of C in H3 (use 4 decimals, example: 1.2345) | |||||||||||||
| 11 | 62 | Show the optimal SSE value that you are able to achieve using your prediction technique in cell E2 |
|||||||||||||
| 12 | 75 | 4) Predict Sales for months 24, 25, and 26. Enter the values in B25, B26, and B27. |
|||||||||||||
| 13 | 91 | ||||||||||||||
| 14 | 105 | 5) Plotactual sales (Y) andyour forecast of sales (Y hat) for all months (i.e. 1 to 26) and show it below. |
|||||||||||||
| 15 | 122 | ||||||||||||||
| 16 | 131 | ||||||||||||||
| 17 | 151 | ||||||||||||||
| 18 | 179 | ||||||||||||||
| 19 | 203 | ||||||||||||||
| 20 | 226 | ||||||||||||||
| 21 | 249 | ||||||||||||||
| 22 | 282 | ||||||||||||||
| 23 | 309 | ||||||||||||||
| 24 | ?? | ||||||||||||||
| 25 | ?? | ||||||||||||||
| 26 | ?? |
ScholarMatic: Explanation & Answer
Your ready answer from a verified tutor is just a click away for as little as $14.99
Click Order Now to get 100% Original Answer Customized to your instructions!
