R Mean, Median, and Mode

Mean, Mode, and Median are measurements of central tendency. In other words, it tells you where the "middle" of a data set is.

Each of these statistics defines the middle differently.

• The mean is the average of a data set.
• The mode is the most common number in a data set.
• The median is the middle of the set of numbers.

If you want to learn more in detail about measurements of central tendency, please visit Mean, Median, and Mode.

Calculate Mean in R

In R, we use the mean() function to calculate the mean. For example,

# vector of marks
marks <- c(97, 78, 57, 64, 87)

# calculate average marks
result <- mean(marks)

print(result)

Output

[1] 76.6

In the above example, we have used the mean() function to calculate the average result of the marks vector.

Calculate Median in R

We use the median() function to calculate the median in R. For example,

# vector of marks
marks <- c(97, 78, 57, 64, 87)

# find middle number of marks
result <- median(marks)

print(result)

Output

[1] 78

In the above example, we have used the median() function to find the middle value of the marks vector.

Calculate Mode in R

In R, unlike mean and median, there's no built-in function to calculate mode. We need to create a user defined function to calculate mode. For example,

# vector of marks
marks <- c(97, 78, 57,78, 97, 66, 87, 64, 87, 78)

# define mode() function
mode = function() {
  
  # calculate mode of marks  
  return(names(sort(-table(marks)))[1])
}

# call mode() function
mode()

Output

[1] "78"

In the above example, we have created a function named mode() to calculate the mode of the marks vector.

Inside the function, we have used the table() function to create a categorical representation of data with the variable names and the frequency in the form of a table.

We will sort marks in descending order and will return the 1st value from the sorted values.

Finally, we have called the mode() function and it returned the most common number in marks i.e. 78

Note: We have used vectors to demonstrate how to calculate mean, median, and mode. We can also calculate mean, median, and mode from CSV file, larger datasets, etc in a similar way.