You can use the following syntax to calculate the standard deviation of a vector in R:
sd(x)
Note that this formula calculates the sample standard deviation using the following formula:
√Σ (xi – μ)2/ (n-1)
where:
- Σ: A fancy symbol that means “sum”
- xi: The ith value in the dataset
- μ: The mean value of the dataset
- n: The sample size
The following examples show how to use this function in practice.
Example 1: Calculate Standard Deviation of Vector
The following code shows how to calculate the standard deviation of a single vector in R:
#create dataset
data #find standard deviation
sd(data)
[1] 8.279157
Note that you must use na.rm = TRUE to calculate the standard deviation if there are missing values in the dataset:
#create dataset with missing values data #attempt to find standard deviation sd(data) [1] NA #find standard deviation and specify to ignore missing values sd(data, na.rm = TRUE) [1] 9.179753
Example 2: Calculate Standard Deviation of Column in Data Frame
The following code shows how to calculate the standard deviation of a single column in a data frame:
#create data frame data frame(a=c(1, 3, 4, 6, 8, 9), b=c(7, 8, 8, 7, 13, 16), c=c(11, 13, 13, 18, 19, 22), d=c(12, 16, 18, 22, 29, 38)) #find standard deviation of column a sd(data$a) [1] 3.060501
Example 3: Calculate Standard Deviation of Several Columns in Data Frame
The following code shows how to calculate the standard deviation of several columns in a data frame:
#create data frame data frame(a=c(1, 3, 4, 6, 8, 9), b=c(7, 8, 8, 7, 13, 16), c=c(11, 13, 13, 18, 19, 22), d=c(12, 16, 18, 22, 29, 38)) #find standard deviation of specific columns in data frame apply(data[ , c('a', 'c', 'd')], 2, sd) a c d 3.060501 4.289522 9.544632
Additional Resources
How to Find the Range in R
How to Calculate Sample & Population Variance in R
How to Remove Outliers in R