1. Problem: Determine the linear regression equation that provides the "best" estimate of peak-hour trips attracted for the 16 zones listed in Table 1. Based on the best model selected, conduct empirical analysis on all independent variables and the intercept. (20 pts) Table 1. Peak-hour Trips of 16 Zones Employment Zone Total Peak-hour trips attracted No. Manufacturing Other Retail and service (X3) (X) 1 9,482 6,820 2,547 115 10,428 2 2,010 111 1,899 0 2.192 3 574 228 87 259 330 4 127 0 127 0 153 3,836 2.729 813 294 3,948 953 101 773 79 1,188 7 223 165 58 240 36 6 30 0 55 9 2.223 1,550 499 174 2,064 10 272 166 280 11 50 0 48 2 72 12 209 36 173 0 230 13 410 140 7 263 420 14 11,023 10,932 63 28 10,654 15 527 188 14 450 16 183 123 59 1 130 oltino 0 coa 106 325 Notes: Please use Excel or SPSS to conduct the regression and attach your Excel (.xls xlsx), SPSS (-spv). or Matlab(.m) files. Submission without openable files will be graded on a 10pt basis. 1. Problem: Determine the linear regression equation that provides the "best" estimate of peak-hour trips attracted for the 16 zones listed in Table 1. Based on the best model selected, conduct empirical analysis on all independent variables and the intercept. (20 pts) Table 1. Peak-hour Trips of 16 Zones Employment Zone Total Peak-hour trips attracted No. Manufacturing Other Retail and service (X3) (X) 1 9,482 6,820 2,547 115 10,428 2 2,010 111 1,899 0 2.192 3 574 228 87 259 330 4 127 0 127 0 153 3,836 2.729 813 294 3,948 953 101 773 79 1,188 7 223 165 58 240 36 6 30 0 55 9 2.223 1,550 499 174 2,064 10 272 166 280 11 50 0 48 2 72 12 209 36 173 0 230 13 410 140 7 263 420 14 11,023 10,932 63 28 10,654 15 527 188 14 450 16 183 123 59 1 130 oltino 0 coa 106 325 Notes: Please use Excel or SPSS to conduct the regression and attach your Excel (.xls xlsx), SPSS (-spv). or Matlab(.m) files. Submission without openable files will be graded on a 10pt basis