Calculate Standard Error in R
Last Updated :
07 Sep, 2021
In this article, we are going to see how to calculate standard error in R Programming Language.
Mathematically we can calculate standard error by using the formula:
standard deviation/squareroot(n)
In R Language, we can calculate in these ways:
- Using sd() function with length function
- By using the standard error formula.
- Using plotrix package.
Method 1 : Using sd() function with length function
Here we are going to use sd() function which will calculate the standard deviation and then the length() function to find the total number of observation.
Syntax: sd(data)/sqrt(length((data)))
Example: R program to calculate a standard error from a set of 10 values in a vector
R
a < - c (179, 160, 136, 227, 123, 23,
45, 67, 1, 234)
print ( sd (a)/ sqrt ( length ((a))))
|
Output:
[1] 26.20274
Method 2: By using standard error formula
Here we will use the standard error formula for getting the observations.
Syntax: sqrt(sum((a-mean(a))^2/(length(a)-1)))/sqrt(length(a))
where
- data is the input data
- sqrt function is to find the square root
- sum is used to find the sum of elements in the data
- mean is the function used to find the mean of the data
- length is the function used to return the length of the data
Example: R program to calculate the standard error using formula
R
a <- c (179, 160, 136, 227, 123, 23,
45, 67, 1, 234)
print ( sqrt ( sum ((a - mean (a)) ^ 2/( length (a) - 1)))
/ sqrt ( length (a)))
|
Output:
[1] 26.20274
Method 3 : Using std.error() function( plotrix package)
This is the built-in function that directly calculated the standard error. It is available in plotrix package
Syntax: std.error(data)
Example: R program to calculate the standard error using std.error()
R
library ( "plotrix" )
a <- c (179,160,136,227,123,
23,45,67,1,234)
print ( std.error (a))
|
Output:
[1] 26.20274
Share your thoughts in the comments
Please Login to comment...