自己试试就知道了啊。下面就是两个变量的例子啊。
************************************************
sysuse auto,clear
regress mpg weight foreign
*F test
test foreign
return list
di r(F)^0.5
test weight
return list
di r(F)^0.5
*************************************************
. sysuse auto,clear
(1978 Automobile Data)
. regress mpg weight foreign
Source | SS df MS Number of obs = 74
-------------+------------------------------ F( 2, 71) = 69.75
Model | 1619.2877 2 809.643849 Prob > F = 0.0000
Residual | 824.171761 71 11.608053 R-squared = 0.6627
-------------+------------------------------ Adj R-squared = 0.6532
Total | 2443.45946 73 33.4720474 Root MSE = 3.4071
------------------------------------------------------------------------------
mpg | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
weight | -.0065879 .0006371 -10.34 0.000 -.0078583 -.0053175
foreign | -1.650029 1.075994 -1.53 0.130 -3.7955 .4954422
_cons | 41.6797 2.165547 19.25 0.000 37.36172 45.99768
------------------------------------------------------------------------------
.
. *F test
. test foreign
( 1) foreign = 0
F( 1, 71) = 2.35
Prob > F = 0.1296
. return list
scalars:
r(drop) = 0
r(df_r) = 71
r(F) = 2.351599804945212
r(df) = 1
r(p) = .1295987008429732
. di r(F)^0.5
1.5334927
.
. test weight
( 1) weight = 0
F( 1, 71) = 106.92
Prob > F = 0.0000
. return list
scalars:
r(drop) = 0
r(df_r) = 71
r(F) = 106.9200998079409
r(df) = 1
r(p) = 8.28287059135e-16
. di r(F)^0.5
10.340218
.
end of do-file