search for: s_regression

...ing assumes some relation between the easily/ fast received x-information and the elaborate/ time-consuming y-information, say a ratio r=sum y (phase2)/ sum x (phase2)=15/10=1.5 (out of the above table) Ergo, the y.ratio estimator = r*x.bar(phase1) = 1.5*0.08 = 0.12 with variance = (n1-n2)/n1 * s_regression^2/n2 + s_y^2/n1 = 900/1000 * 0.0765/100 + 0.129/1000 = .00081 SE .02846 with s_regression^2 = yk=c(rep(0,85), rep(1,15)); xk=c(rep(0,90), rep(1,10)) 1/98*sum((yk-1.5*xk)^2) and s_yk^2 = 1/99 * sum( (yk-.15)^2)=0.1287879 I am sorry to bother you with my false calculations, but I just don't k...