例题09-04(例 ): predict yhat(option xb assumed; fitted values) predict seyhat,stdp gen CL=yhat-invttail(6,0025)*seyhat gen CU=yhat+invttail(6,0025)*seyhat predict sey,stdf gen RL=yhat-invttail(6,0025)*
例题04-09 (例 ) anovaweight group treat Number of obs =15 R-squared =08566 Root MSE= 097724 Adj R-squared =07490Source |Partial SSdf MS F ProbF-----------+----------------------------------------------
例题04-04 (例 ) anovaweight treat group Number of obs =15 R-squared =08566 Root MSE= 097724 Adj R-squared =07490Source |Partial SSdf MS F ProbF-----------+----------------------------------------------
例题09-09(例): gen w=1/(x*x) reg y x [weight=w](analytic weights assumed)(sum of wgt is 20932e+02)Source | SS df MSNumber of obs =10-------------+------------------------------ F(1, 8) = 7253 Model |28
例题03-04 ttesti 29 2010 702 32 1689 846Two-sample t test with equal variances------------------------------------------------------------------------------ | ObsMeanStd Err Std Dev [95% Conf Interval
例24-04(): corr t1 t2(obs=50) | t1 t2-------------+------------------t1 | 10000t2 | 08203 10000 ttest t1=t2Paired t test------------------------------------------------------------------------------V
例 04-03 drop _all set obs 15obs was 0, now 15 set seed 0 gen weight=uniform() sort weight gen block=group(5) set seed 1 gen suijishu=uniform() sort block suijishu egen treat=seq(),t(3) sort weight l
例题04-06 (例 ) anovax person treat phase Number of obs =20 R-squared =09993 Root MSE= 702673 Adj R-squared =09983Source |Partial SSdf MS F ProbF-----------+--------------------------------------------
例 08-04 (例 ) expand freq(1 zero count ignored; observation not deleted)(70 observations created) dropif freq==0(1 observation deleted) ranksum hanliang ,by(group)Two-sample Wilcoxon rank-sum (Mann-W
例题02-04(例 ) means xVariable |TypeObsMean [95% Conf Interval]-------------+---------------------------------------------------------- x | Arithmetic 554 -2132307 1293231|Geometric 534822029715194 124
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