# Geometric mean using R with examples

In this tutorial, you will learn about what is geometric mean, when to use geometric mean and how to calculate geometric mean in R.

## What is geometric mean?

Geometric mean is a measure of central tendency. It is useful in averaging rate of changes when ratio changes are more important that the absolute changes.

Let $x_i, i=1,2, \cdots , n$ be $n$ positive observations
then the geometric mean of $X$ is denoted by $GM$ and is is defined as

 \begin{aligned} GM &=\big(\prod_{i=1}^n x_i\big)^{1/n}\\ &=\sqrt[n]{x_1\times x_2\times \cdots \times x_n} \end{aligned}

Thus, the geometric mean is the $n^{th}$ root of the product of all the observations.

## When to use geometric mean?

Geometric mean is often used in averaging the data about rates and ratios. Geometric mean is commonly used measure of central tendency in finance to calculate average rate of interest, average growth rate or average return on financial portfolio.

## How to calculate geometric mean in R?

As such there is no specific function available in base package. But you can define your own function for geometric mean or use geometric.mean() function from psych package.

### Geometric mean using user-defined function

Let us create a user-defined function to calculate geometric mean as follows:

Geometric.Mean <- function(x, na.rm = TRUE) {
if (na.rm == FALSE & any(is.na(x))) {
avg <- NA
} else{
avg <- exp(mean(log(x), na.rm = TRUE))
}
return(avg)
}

### Using geometric.mean() function from psych package

One can use the geometric.mean() function from psych package. First you need to install the psych package using install.packages("psych"). Once the package is installed, then load the package using library(psych).

The syntax of the geometric.mean() function is

geometric.mean(x,na.rm=TRUE)

where,

• x : a vector, matrix or data.frame,
• na.rm : na.rm=TRUE (default) remove NA values before processing.

For more information about psych package check this link psych package.

Note that, geometric mean is not particularly useful if there are elements that are less than or equal to zero ($\leq 0$).

## Numerical example on geometric mean using R

### Example 1: Geometric Mean Using R

The annual percentage growth rate of profits of a company from year 2010 to 2014 are as follows:

Year 2010 2011 2012 2013 2014
Growth rate (in %) 30 40 76 69 95

Calculate the average annual percentage growth rate of profit.

#### Geometric mean using formula

Geometric mean is the $n^{th}$ root of the product of all the observations. That is

$$GM =\big(\prod_{i=1}^n x_i\big)^{1/n}$$

# create a data vector
x <- c(30, 40,76, 69, 95)
# compute no. of observations in x
n <- length(x)
# calculate geometric mean
GM <- (prod(x)) ** (1 / n)
GM
 56.92637

The average annual percentage growth rate of profit is 56.9263721.

#### Geometric mean using user-defined function

Earlier we have defined the function for geometric mean as Geometric.Mean(x). Let us calculate the geometric mean using user-defined function Geometric.Mean(x).

# create a data vector
x <- c(30, 40,76, 69, 95)
Geometric.Mean(x)
 56.92637

The average annual percentage growth rate of profit is 56.9263721.

#### Geometric mean using psych package

One can use geometric.mean() function from psych package to calculate geometric mean.

# load the package
library(psych)
# use the function to compute geometric mean
geometric.mean(x)
 56.92637

The average annual percentage growth rate of profit is 56.9263721.

### Example 2: Geometric Mean using R with NA's

Calculate the geometric mean of data 10,25,36,23,NA,17.

#### Geometric mean using formula

Geometric mean is the $n^{th}$ root of the product of all the observations. Using the formula

$$GM =\big(\prod_{i=1}^n x_i\big)^{1/n}$$

# create a data vector
x <- c(10,25,36,23,NA,17)
# compute no. of observations in x
n <- length(x[!is.na(x)])
# calculate geometric mean
GM <- (prod(x,na.rm=TRUE)) ** (1 / n)
GM
 20.38374

The geometric mean of given data is 20.3837392.

Note that the default value of na.rm is FALSE in prod() function. Therefore, to remove NA values before processing use the argument na.rm=TRUE. Also to get the length of x without NA use a logical NOT with is.na(x).

#### Geometric mean using user-defined function

Use the user-defined function Geometric.Mean(x) with additional argument na.rm=TRUE.

# create a data vector
x <- c(10,25,36,23,NA,17)
Geometric.Mean(x)
 20.38374

The geometric mean of given data is 20.3837392.

Note that the default value of na.rm is TRUE in our user-defined function Geometric.Mean() function. Therefore, no need to specify the argument na.rm=TRUE.

#### Geometric mean using psych package

Use geometric.mean() function from psych package to calculate geometric mean.

# load the package
library(psych)
# use the function to compute harmonic mean
geometric.mean(x)
 20.38374

The geometric mean of given data is 20.3837392.

Note that the default value of na.rm is TRUE in geometric.mean() function from psych package. Therefore, the NA values are removed before processing.

## Endnote

In this tutorial, you learned about what is geometric mean and how to compute geometric mean for the data using R.

To learn more about descriptive statistics using R, please refer to the following tutorials:

Hopefully you enjoyed this tutorial on geometric mean using R. VRCBuzz co-founder and passionate about making every day the greatest day of life. Raju is nerd at heart with a background in Statistics. Raju looks after overseeing day to day operations as well as focusing on strategic planning and growth of VRCBuzz products and services. Raju has more than 25 years of experience in Teaching fields. He gain energy by helping people to reach their goal and motivate to align to their passion. Raju holds a Ph.D. degree in Statistics. Raju loves to spend his leisure time on reading and implementing AI and machine learning concepts using statistical models.