If you supose that each mean is independent then
s.err_total_chem <- sqrt(sum(s.err_event^2))
If not you must estimate de var-covariance matrix to find this s.err. This estimation will be difficult given the scarce data available.
Hope it will helps.
Kenneth
Jose A. Hernandez wrote:
Folks,
This is so simple is driving me crazy. It's not really an R question is more an Statistics question.
I applied a chemical in 3 different events during a growing season. I took 3 samples in each event to estimate mean applied chemical.
Thus, I can easily estimate means and st.err by event. I can then estimate the total chemical applied for the whole season by adding the 3 means for each event. How can I estimate the standard error of this total applied chemical.
Thanks in advance,
Jose
event <- c(1,1,1,2,2,2,3,3,3) chem <- c(131.75,125.92,130.09,42.67,48.26,54.56,85.05,91.17,90.86) d.1 <- data.frame(event,chem) attach(d.1) s.err <- function(x) sd(x)/(sqrt(length(x)))
print(mean_event <- tapply(d.1$chem,factor(data.1$event),mean)) print(s.err_event <- tapply(d.1$chem,factor(data.1$event),s.err))
print(total_chem <- sum(mean_event)) s.err_total_chem <-
-- Kenneth Roy Cabrera Torres Celular +57 (315) 504 9339
______________________________________________ [EMAIL PROTECTED] mailing list https://www.stat.math.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide! http://www.R-project.org/posting-guide.html
