A traffic engineer develops a linear model for predicting Annual Average Daily Traffic on some arterial road in a governorate based on a sample of size 550 sampling points. The equation is AADT = 16500 + 0.3X1 + 0.17X2 where X1 is the population of the governorate in thousands, and X2 is the number of vehicles registered in the governor. The mean values for , X1 and X2 are x-500 and x,- 13000, and their standard deviations are - 120 and -- 1130, respectively. Upon further research, the engineer finds another linear model for the same road with an equation AADT = 18500 + 0.02X1 +0.04X2, this new equation was based on 800 sample points and the average values of AADT, X1 and X2 were 7,- 450, and x,-14300, respectively, and their standard deviations were 140 and - 1340, respectively. Use the information from the two models to combine them into a new more accurate linear model for predicting the AADT in that governorate. Assume the data are all normally distributed and they were collected almost over the same period of time. Also assume that both X1 and X2 are independent in both studies.