The variance of a sum is the sum of all the elements of the
variance-covariance matrix. If the summands are uncorrelated, then the
variance of the sum is the sum of the variances. hope this helps.
spencer graves
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 <-
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