Jim Brennan wrote:
Was just looking at this data and tried this:
event.var<--tapply(d.1$chem,factor(d.1$event),var) event.var
1 2 3 -9.022233 -35.385033 -11.884433
Any idea why the variances are coming out negative.
Yes, I think you meant:
event.var <- tapply(d.1$chem,factor(d.1$event),var)
(note: second dash negated your result)
var(d.1$chem[1:3])
[1] 9.022233
right number ....
Anyway here is the answer I got if we assume independant means-- and I don't see why not to with the info given.
sqrt(sum(s.err_event^2))
[1] 4.331732
(sum(event.var/3*-1)^.5) [1] 4.331732
----- Original Message ----- From: "Kenneth Cabrera" <[EMAIL PROTECTED]> To: <[EMAIL PROTECTED]>; <[EMAIL PROTECTED]> Sent: Thursday, July 22, 2004 7:27 PM Subject: Re: [R] Standard error of a sum
If you supose that each mean is independent then
s.err_total_chem <- sqrt(sum(s.err_event^2))
If not you must estimate de var-covariance matrix to find this s.err. This estimation will be difficult given the scarce data available.
Hope it will helps.
Kenneth
Jose A. Hernandez wrote:
Folks,
This is so simple is driving me crazy. It's not really an R question is more an Statistics question.
I applied a chemical in 3 different events during a growing season. I took 3 samples in each event to estimate mean applied chemical.
Thus, I can easily estimate means and st.err by event. I can then estimate the total chemical applied for the whole season by adding the 3 means for each event. How can I estimate the standard error of this total applied chemical.
Thanks in advance,
Jose
event <- c(1,1,1,2,2,2,3,3,3) chem <- c(131.75,125.92,130.09,42.67,48.26,54.56,85.05,91.17,90.86) d.1 <- data.frame(event,chem) attach(d.1) s.err <- function(x) sd(x)/(sqrt(length(x)))
print(mean_event <- tapply(d.1$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
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