So it doesn't look like the weight has an effect on the min and max, but that it does on everyother value.
proc univariate data=sashelp.bweight noprint; var Weight; weight MomWtGain; output out=goofy1 min=min max=max mean=mean p10=p10 q1=q1 q3=q3; run; proc univariate data=sashelp.bweight noprint; var Weight; output out=goofy2 min=min max=max mean=mean p10=p10 q1=q1 q3=q3; run; proc means data=sashelp.bweight noprint; var Weight; weight MomWtGain; output out=goofy3 min=min max=max mean=mean p10=p10 q1=q1 q3=q3; run; proc univariate data=sashelp.bweight noprint; var Weight; output out=goofy4 min=min max=max mean=mean p10=p10 q1=q1 q3=q3; run; proc sql; create table goofy as select distinct min, max, mean, p10, q1, q3, "Univariate no weight" as type from goofy2 union corr select distinct min, max, mean, p10, q1, q3, "Univariate weighted" as type from goofy1 union corr select distinct min, max, mean, p10, q1, q3, "Means no weight" as type from goofy4 union corr select distinct min, max, mean, p10, q1, q3, "Means weighted" as type from goofy3;
However thats because a weight statement only makes that observation more valuable to the statistic, it doesn't actually change the real value of the variable. Hence the reason that the min and max never change, but the computed statistics do change. Oh and there is no difference between proc means and proc univariate outputs, thats what the above shows.
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