---------------------------------------------------------------------------------------------------------- name: log: C:\Users\Aki\Documents\stata\april4.log log type: text opened on: 4 Apr 2022, 18:16:41 . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . sysuse auto, clear (1978 Automobile Data) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . use nlsw, clear (NLSW, 1988 extract) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . graph box wage, over(country) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . sort wage country . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . hist wage, by(country) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . help regress . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . sysuse auto, clear (1978 Automobile Data) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . reg price mpg weight length Source | SS df MS Number of obs = 74 -------------+---------------------------------- F(3, 70) = 12.98 Model | 226957412 3 75652470.6 Prob > F = 0.0000 Residual | 408107984 70 5830114.06 R-squared = 0.3574 -------------+---------------------------------- Adj R-squared = 0.3298 Total | 635065396 73 8699525.97 Root MSE = 2414.6 ------------------------------------------------------------------------------ price | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- mpg | -86.78928 83.94335 -1.03 0.305 -254.209 80.63046 weight | 4.364798 1.167455 3.74 0.000 2.036383 6.693213 length | -104.8682 39.72154 -2.64 0.010 -184.0903 -25.64607 _cons | 14542.43 5890.632 2.47 0.016 2793.94 26290.93 ------------------------------------------------------------------------------ . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . reg price mpg weight length i.rep78 i.foreign Source | SS df MS Number of obs = 69 -------------+---------------------------------- F(8, 60) = 9.65 Model | 324598377 8 40574797.1 Prob > F = 0.0000 Residual | 252198582 60 4203309.7 R-squared = 0.5628 -------------+---------------------------------- Adj R-squared = 0.5045 Total | 576796959 68 8482308.22 Root MSE = 2050.2 ------------------------------------------------------------------------------ price | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- mpg | -37.70139 79.68181 -0.47 0.638 -197.0887 121.686 weight | 6.045295 1.073279 5.63 0.000 3.898417 8.192172 length | -105.5752 36.48828 -2.89 0.005 -178.5627 -32.5878 | rep78 | 2 | 893.7844 1628.744 0.55 0.585 -2364.189 4151.757 3 | 802.7751 1504.123 0.53 0.596 -2205.918 3811.469 4 | 843.8791 1576.237 0.54 0.594 -2309.063 3996.822 5 | 1618.893 1713.585 0.94 0.349 -1808.788 5046.574 | foreign | Foreign | 3277.552 849.3603 3.86 0.000 1578.579 4976.526 _cons | 6569.534 5933.985 1.11 0.273 -5300.203 18439.27 ------------------------------------------------------------------------------ . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . predict priceb, xb (5 missing values generated) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . predict residual, residuals (5 missing values generated) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . summarize priceb residual Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- priceb | 69 6146.043 2184.835 1212.799 11580.09 residual | 69 1.38e-07 1925.825 -3969.608 5525.199 . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . sum price Variable | Obs Mean Std. Dev. Min Max -------------+--------------------------------------------------------- price | 74 6165.257 2949.496 3291 15906 . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . kdensity residual . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . gen lprice = log(price) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . reg lprice mpg weight length i.rep78 i.foreign Source | SS df MS Number of obs = 69 -------------+---------------------------------- F(8, 60) = 11.00 Model | 6.08754955 8 .760943693 Prob > F = 0.0000 Residual | 4.14989653 60 .069164942 R-squared = 0.5946 -------------+---------------------------------- Adj R-squared = 0.5406 Total | 10.2374461 68 .150550678 Root MSE = .26299 ------------------------------------------------------------------------------ lprice | Coef. Std. Err. t P>|t| [95% Conf. Interval] -------------+---------------------------------------------------------------- mpg | -.0076699 .0102213 -0.75 0.456 -.0281156 .0127757 weight | .0007187 .0001377 5.22 0.000 .0004433 .0009941 length | -.0105475 .0046806 -2.25 0.028 -.0199101 -.0011849 | rep78 | 2 | .0778632 .2089297 0.37 0.711 -.3400584 .4957847 3 | .0824566 .1929437 0.43 0.671 -.3034883 .4684015 4 | .1397924 .2021942 0.69 0.492 -.2646563 .544241 5 | .2085164 .2198128 0.95 0.347 -.2311747 .6482075 | foreign | Foreign | .4784783 .108953 4.39 0.000 .2605398 .6964168 _cons | 8.349292 .7611912 10.97 0.000 6.826683 9.871902 ------------------------------------------------------------------------------ . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . predict lpriceb, xb (5 missing values generated) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . rename residual residual1 . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . predict residual, residuals (5 missing values generated) . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . kdensity residual . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . rvfplot . end of do-file . do "C:\Users\Aki\AppData\Local\Temp\STD28e8_000000.tmp" . log close name: log: C:\Users\Aki\Documents\stata\april4.log log type: text closed on: 4 Apr 2022, 19:29:28 ----------------------------------------------------------------------------------------------------------