During year three, Pricilla starting collecting data on why people were buying dresses. She and the people working in the store would ask whether the purchase was for an event (homecoming, party, prom, or wedding. You noticed that sells were higher in warmer months and decided to use average month temperatures. Also, you decided the separate weddings from other events. The following is a breakdown of the data.

Wedding	Events	Average Monthly Temperature	Year 3 Demand
2	1	32		212
0	0	30		245
0	5	42		252
12	22	50		376
45	46	55		757
23	22	70		404
20	20	75		354
10	20	78		324
2	32	75		338
1	50	60		618
1	22	45		356
8	60	35		713
				4949

Using the dress data above, calculate the following

1. Use Excels regression function to develop a multiple regression forecast for Pricilla Phashions

2. Indicate the r² of the model, and whether all the coefficients for the regression are significant.

3. Using your regression model, calculate the dress sales for Year-3.

4. Using the actual Year-3 numbers check your forecast accuracy, by calculating CFE, MSE, MAD, MAPE, and the tracking signal

5. Finally, compare the causal forecast model you just developed to the best model that you developed previously. Recommend which forecasting model should Pricilla use.