In R, how to find the standard error of the mean?

Question

Is there any command to look for the standard error of the mean in R?

Answer 1

There the plotrix package has a built-in function for this: std.error

Answer 2

The standard error is the standard deviation divided by the square root of the sample size. This way you can easily make your own function:

> std <- function(x) sd(x)/sqrt(length(x)) > std(c(1,2,3,4)) [1] 0.6454972 

Answer 3

It is probably more efficient to use var ... since you actually sqrt twice in your code, once to get sd (the code for sd is in r and displayed by typing "sd") ...

 se <- function(x) sqrt(var(x)/length(x)) 

Answer 4

John's version of the answer above that removes annoying NA:

 stderr <- function(x, na.rm=FALSE) { if (na.rm) x <- na.omit(x) sqrt(var(x)/length(x)) } 

Answer 5

The packet multiplier has a built-in se (x) function

Answer 6

more generally, for standard errors for any other parameter, you can use the boot package to simulate the boot (or write them yourself)

Answer 7

Try this https://www.rdocumentation.org/packages/psych/versions/1.8.12/topics/describe. I think this is a psycho package.

Answer 8

 y <- mean(x, na.rm=TRUE) 

sd(y) for standard deviation var(y) for variance.

Both pins use n-1 in the denominator, so they are based on sample data.