估计问题太弱了..........哭等...........

. pwcorr api00 acs_k3 avg_ed grad_sch col_grad some_col, star(.05)
| api00   acs_k3   avg_ed  grad_sch  col_grad  some_col
-------------+------------------------------------------------------
   api00 | 1.0000
  acs_k3 | 0.1710* 1.0000
  avg_ed | 0.7930* 0.0794 1.0000
grad_sch | 0.6332* 0.0983* 0.7973* 1.0000
col_grad | 0.5273* -0.0174 0.8089* 0.4439* 1.0000
some_col | 0.2615* 0.0915 0.3031* 0.0718 0.1555* 1.0000
. regress api00 acs_k3 avg_ed grad_sch col_grad some_col
  Source |  SS        df   MS                       Number of obs = 379
-------------+------------------------------           F( 5, 373) = 143.79
   Model | 5056268.54  5   1011253.71                 Prob > F = 0.0000
Residual | 2623191.21  373 7032.68421                    R-squared = 0.6584
-------------+------------------------------           Adj R-squared = 0.6538
   Total | 7679459.75  378  20316.0311                         Root MSE = 83.861
------------------------------------------------------------------------------
   api00 | Coef. Std. Err. t P>|t| [95% Conf. Interval]
-------------+----------------------------------------------------------------
  acs_k3 | 11.45725 3.275411 3.50 0.001 5.016669 17.89784
  avg_ed | 227.2638 37.2196 6.11 0.000 154.0773 300.4504
grad_sch | -2.090898 1.352292 -1.55 0.123 -4.749969 .5681735
col_grad | -2.967831 1.017812 -2.92 0.004 -4.969199 -.9664626
some_col | -.7604543 .8109676 -0.94 0.349 -2.355096 .8341872
_cons | -82.60913 81.84638 -1.01 0.313 -243.5473 78.32904
------------------------------------------------------------------------------

. vif
Variable | VIF   1/VIF
-------------+----------------------
  avg_ed | 43.57  0.022951
grad_sch | 14.86  0.067274
col_grad | 14.78  0.067664
some_col | 4.07   0.245993
a  cs_k3 | 1.03     0.971867
-------------+----------------------
Mean VIF | 15.66
. regress api00 acs_k3 grad_sch col_grad some_col
  Source | SS          df        MS                       Number of obs = 398
-------------+------------------------------            F( 4, 393) = 107.12
   Model | 4180144.34   4      1045036.09                    Prob > F = 0.0000
Residual | 3834062.79  393    9755.88497                     R-squared = 0.5216
-------------+------------------------------               Adj R-squared = 0.5167
Total | 8014207.14      397    20186.9197                         Root MSE = 98.772
------------------------------------------------------------------------------
   api00 | Coef.      Std. Err. t   P>|t|         [95% Conf. Interval]
-------------+----------------------------------------------------------------
  acs_k3 | 11.7126   3.664872  3.20   0.002   4.507392     18.91781
grad_sch | 5.634762  .4581979  12.30   0.000   4.733936     6.535588
col_grad | 2.479916  .3395548  7.30    0.000    1.812345     3.147487
some_col | 2.158271  .4438822  4.86   0.000     1.28559     3.030952
   _cons | 283.7446  70.32475  4.03   0.000    145.4848     422.0044
------------------------------------------------------------------------------
. vif
Variable | VIF 1/VIF
-------------+----------------------
col_grad | 1.28 0.782726
grad_sch | 1.26 0.792131
some_col | 1.03 0.966696
  acs_k3 | 1.02 0.976666
-------------+----------------------
Mean VIF | 1.15

问第一次回归是否有多重？如何判断的？

2.vif of avg-ed ？

3.如何解决问题？

 大侠们我把试题贴出来了，拜托拜托

第一次回归不存在多重共线性，因为经验分析，如果vif的值小于10，则会接受原假设，认为不存在多重共线性