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# Stata Markdown

Let us read the fuel efficiency data that is shipped with Stata

``````. sysuse auto, clear
(1978 Automobile Data)

``````

To study how fuel efficiency depends on weight it is useful to transform the dependent variable from “miles per gallon” to “gallons per 100 miles”

``````.     gen gphm = 100/mpg

``````

We then obtain a more linear relationship

``````.     twoway scatter gphm weight || lfit gphm weight ///
>         , ytitle(Gallons per Mile) legend(off)

``````

The regression equation estimated by OLS is

``````.         regress gphm weight

Source |       SS           df       MS      Number of obs   =        74
-------------+----------------------------------   F(1, 72)        =    194.71
Model |  87.2964969         1  87.2964969   Prob > F        =    0.0000
Residual |  32.2797639        72  .448330054   R-squared       =    0.7300
Total |  119.576261        73  1.63803097   Root MSE        =    .66957

------------------------------------------------------------------------------
gphm |      Coef.   Std. Err.      t    P>|t|     [95% Conf. Interval]
-------------+----------------------------------------------------------------
weight |    .001407   .0001008    13.95   0.000      .001206    .0016081
_cons |   .7707669   .3142571     2.45   0.017     .1443069    1.397227
------------------------------------------------------------------------------

``````

Thus, a car that weighs 1,000 lbs more than another requires on average an extra 1.4 gallons to travel 100 miles.

That’s all for now!