Econometric take home APPS_Part_19

Econometric take home APPS_Part_19 - F |.16237770.05703645...

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75 +--------+--------------+----------------+--------+--------+----------+ F | .16237770 .05703645 2.847 .0111 231.470000 C | .00310174 .02196531 .141 .8894 486.765000 Constant| 22.7071160 6.87207605 3.304 .0042 +----------------------------------------------------+ | Residuals Sum of squares = 1110.533 | | Standard error of e = 8.082418 | | Fit R-squared = .9521422 | +----------------------------------------------------+ +--------+--------------+----------------+--------+--------+----------+ |Variable| Coefficient | Standard Error |t-ratio |P[|T|>t]| Mean of X| +--------+--------------+----------------+--------+--------+----------+ F | .13145484 .03117234 4.217 .0006 419.865000 C | .08537427 .10030597 .851 .4065 104.285000 Constant| -8.68554338 4.54516804 -1.911 .0730 +----------------------------------------------------+ | Residuals Sum of squares = 1507.403 | | Standard error of e = 9.416516 | | Fit R-squared = .7635009 | +----------------------------------------------------+ +--------+--------------+----------------+--------+--------+----------+ |Variable| Coefficient | Standard Error |t-ratio |P[|T|>t]| Mean of X| +--------+--------------+----------------+--------+--------+----------+ F | .08752720 .06562593 1.334 .1999 149.790000 C | .12378141 .01706483 7.254 .0000 314.945000 Constant| -4.49953436 11.2893942 -.399 .6952 +----------------------------------------------------+ | Residuals Sum of squares = 1773.234 | | Standard error of e = 10.21312 | | Fit R-squared = .7444461 | +----------------------------------------------------+ +--------+--------------+----------------+--------+--------+----------+ |Variable| Coefficient | Standard Error |t-ratio |P[|T|>t]| Mean of X| +--------+--------------+----------------+--------+--------+----------+ F | .05289413 .01570650 3.368 .0037 670.910000 C | .09240649 .05609897 1.647 .1179 85.6400000 Constant| -.50939018 8.01528894 -.064 .9501 +----------------------------------------------------+ | Residuals Sum of squares = 1407.360 | | Standard error of e = 9.098674 | | Fit R-squared = .6655145 | +----------------------------------------------------+ +--------+--------------+----------------+--------+--------+----------+ |Variable| Coefficient | Standard Error |t-ratio |P[|T|>t]| Mean of X| +--------+--------------+----------------+--------+--------+----------+ F | .07538794 .03395227 2.220 .0403 333.650000 C | .08210356 .02799168 2.933 .0093 297.900000 Constant| -7.72283708 9.35933952 -.825 .4207 +----------------------------------------------------+ | Residuals Sum of squares = 20.02673 | | Standard error of e = 1.085377 | | Fit R-squared = .6431578 | +----------------------------------------------------+ +--------+--------------+----------------+--------+--------+----------+ |Variable| Coefficient | Standard Error |t-ratio |P[|T|>t]| Mean of X| +--------+--------------+----------------+--------+--------+----------+ F | .00457343 .02716079 .168 .8683 70.9210000 C | .43736919 .07958891 5.495 .0000 5.94150000 Constant| .16151857 2.06556414 .078 .9386

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76 +----------------------------------------------------+ | Ordinary least squares regression | | LHS=I Mean = 145.9582 | | Standard deviation = 216.8753 | | WTS=none Number of observs. = 200 | | Model size Parameters = 3 | | Degrees of freedom = 197 | | Residuals Sum of squares = 1755850. | | Standard error of e = 94.40840 | | Fit
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