*
* Example 4.1 from page 123
*
open data wage1.raw
data(format=free,org=columns) 1 526 wage educ exper tenure nonwhite female married numdep $
  smsa northcen south west construc ndurman trcommpu trade services profserv $
  profocc clerocc servocc lwage expersq tenursq
*
linreg lwage
# constant educ exper tenure
*
* The significance level on the t-statistic is for a two-tailed test. For a
* one-tailed test (as is described in the example), all you need to do is take
* the two-tailed significance level and divide it by 2. The two-tailed p-value on
* exper is 0.01713563; half of that is around .0085, replicating the result cited
* that the statistic is significant even beyond the .01 level. If you want to get
* a "table" critical value, you can use the following instruction:
*
disp %invttest(.02,%ndf)
*
* Note that %invttest again is based upon a two-tailed test, so to get the .01
* one-tailed significance level, you need to request the .02 two-tailed point.
* You'll also note that this is slightly different from the critical value (2.326)
* given in the book - this is because the instruction above gives the critical
* value for a t with 522 degrees of freedom (%ndf is equal to the degrees of
* freedom from the last regression), which is just a bit different from that for
* a normal.