How To Calculate Standard Deviation in R

Base R has a function you can use to calculate standard deviation in R.

The standard deviation is a commonly used measure of the degree of variation within a set of data values. A low standard deviation relative to the mean value of a sample means the observations are tightly clustered; larger values indicate observations are more spread out. Learning how to obtain standard deviation in R is easy, and it’s a statistical function that you will use for the rest of your life.

How to Find Standard Deviation in R

You can calculate standard deviation in R using the sd() function. This standard deviation function is a part of standard R, and needs no extra packages to be calculated.

# set up standard deviation in R example
> test <- c(41,34,39,34,34,32,37,32,43,43,24,32)

# standard deviation R function
# sample standard deviation in r
> sd(test)
[1] 5.501377

As you can see, calculating standard deviation in R is as simple as that- the basic R function computes the standard deviation for you easily. Need to get the standard deviation for an entire data set? Use the sapply () function to map it across the relevant items. For this example, we’re going to use the ChickWeight dataset in Base R. This will help us calculate the standard deviation of columns in R.

# standard deviation in R - dataset example
# using head to show the first handful of records
> head(ChickWeight)
  weight Time Chick Diet
1     42    0     1    1
2     51    2     1    1
3     59    4     1    1
4     64    6     1    1
5     76    8     1    1
6     93   10     1    1

# standard deviation in R - using sapply to map across columns
# how to calculate standard deviation in r data frame
> sapply(ChickWeight[,1:4], sd)
   weight      Time     Chick      Diet 
71.071960  6.758400 13.996847  1.162678 

Learning how to calculate standard deviation in r is quite simple, but an invaluable skill for any programmer. These techniques can be used to calculate sample standard deviation in r, standard deviation of rows in r, and much more. None of the columns need to be removed before computation proceeds, as each column’s standard deviation is calculated.

Need to work with standard error? We’ve got you covered here….

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