var() Function In R: Calculate Variance

Today, we will learn about how to use the var() function in the R programming language. If you want to learn more about this topic, so please read the full this article below.

What is the var() function in R?

The var() function in the R programming language calculates a vector’s sample variance. A measure of variability is called Variance. The average squared departures from the mean are used to determine the Variance. The Variance reveals how widely distributed your dataset is. The Variance around the mean increases with the degree of data separation. Let’s look at the syntax and code example below.

Syntax:

var(x, na.rm = FALSE)

Parameters:

• x: The vector, matrix, …
• na.rm: The default leaving NA values in place is false, and removing them is true.

How to use var() function in R?

var() function: Calculating Variance of a vector

Here, we can create a vector, and we will calculate the Variance of this vector.

# Create a vector
x <- c(6,9,59,4,8,2,3,4,-8,9,6,4)

# Apply var function in R
res <- var(x)
cat('The var is:',res)

Output

The var is: 269.7879

var() function: Calculating Variance of a data frame

As a vector, we can calculate the Variance of a data frame with specific columns in this data frame. Follow the code example below.

First, we will create a data frame as follows:

# Create a data frame
df <- data.frame(
    ID = c(1,2,3,4,5,6,7,8),
    Math = c(6,8,9,6,3,2,4,9),
    Physics = c(8,9,6,4,5,9,7,6),
    English = c(9,5,6,3,2,1,4,8)
)

# View data frame
df

Output

  ID Math Physics English
1  1    6       8       9
2  2    8       9       5
3  3    9       6       6
4  4    6       4       3
5  5    3       5       2
6  6    2       9       1
7  7    4       7       4
8  8    9       6       8

Then we can calculate variance as follows:

# Create a data frame
df <- data.frame(
    ID = c(1,2,3,4,5,6,7,8),
    Math = c(6,8,9,6,3,2,4,9),
    Physics = c(8,9,6,4,5,9,7,6),
    English = c(9,5,6,3,2,1,4,8)
)

# Calculate variance
resMath <- var(df$Math)
resPhysics <- var(df$Physics)
resEnglish <- var(df$English)

# View variance
cat('The var of Math is:',resMath,'\n')
cat('The var of Physics is:',resPhysics,'\n')
cat('The var of English is:',resEnglish)

Output

The var of Math is: 7.267857
The var of Physics is: 3.357143
The var of English is: 7.928571

var() function: Converting Variance to Standard Deviation

As you have learned, the Variance is equal to the square of the standard deviation. Thus we can convert the Variance to the standard deviation by the square root of the method. See the code below:

# Create a vector
x <- c(6,8,9,6,3,2,4,9)

# Calculate the standard deviation through the variance
res <- sqrt(var(x))

# View result
cat('Convert Variance to Standard Deviation:', res)

Output

Convert Variance to Standard Deviation: 2.695896

Here, you can check result by using sd() function in R.

# Create a vector
x <- c(6,8,9,6,3,2,4,9)

# Calculate the standard deviation through the variance
res <- sqrt(var(x))

# Calculate the standard deviation using sd() function
res1 <- sd(x)

# View result
cat('Convert Variance to Standard Deviation:', res,'\n')
cat('The standard deviation', res1)

Output

Convert Variance to Standard Deviation: 2.695896
The standard deviation 2.695896

Summary

This article shares calculated Variance by using the var() function in R language. So, if you have any questions, please comment below.

Have a great day!

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Scott Miller

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