In: Statistics and Probability
| 
 X1  | 
 X2  | 
 X3  | 
 Sales  | 
| 
 0.12  | 
 300000.00  | 
 42000.00  | 
 250000.00  | 
| 
 0.13  | 
 310000.00  | 
 43000.00  | 
 255000.00  | 
| 
 0.11  | 
 315000.00  | 
 44000.00  | 
 258000.00  | 
| 
 0.09  | 
 312000.00  | 
 40000.00  | 
 248000.00  | 
| 
 0.10  | 
 311000.00  | 
 41000.00  | 
 246000.00  | 
| 
 0.13  | 
 324000.00  | 
 42000.00  | 
 250000.00  | 
| 
 0.12  | 
 325000.00  | 
 44000.00  | 
 256000.00  | 
| 
 0.11  | 
 327000.00  | 
 45000.00  | 
 257000.00  | 
| 
 0.11  | 
 329000.00  | 
 45000.00  | 
 263000.00  | 
| 
 0.09  | 
 332000.00  | 
 46000.00  | 
 270000.00  | 
| 
 0.08  | 
 335000.00  | 
 47000.00  | 
 280000.00  | 
| 
 0.08  | 
 339000.00  | 
 48000.00  | 
 290000.00  | 
| 
 0.07  | 
 341000.00  | 
 51000.00  | 
 310000.00  | 
| 
 0.08  | 
 342000.00  | 
 52000.00  | 
 315000.00  | 
| 
 0.11  | 
 339000.00  | 
 49000.00  | 
 290000.00  | 
| 
 0.12  | 
 327000.00  | 
 45000.00  | 
 ?????  | 
1. What is the sales forecast for period 16?
2. Is the forecast statistically significant? Which variable has the largest impact on sales?
2. If this is a forecast for a brick and mortar retailer, what would be the sales forecast if X3 (square feet) was set to 0?