To calculate a weighted mean in R, you can use the built-in function, which uses the following syntax:

weighted.mean(x, w)

where:

• x: A vector of raw data values
• w: A vector of weights

This tutorial shows several examples of how to use this function in practice.

Example 1: Weighted Mean of a Vector

The following code shows how to calculated the weighted mean for a given vector of data:

#define vector of data values
data <- c(3, 5, 6, 7, 8)

#define vector of weights
weights <- c(.1, .3, .3, .2, .1)

#calculate weighted mean
weighted.mean(x=data, w=weights)

[1] 5.8

The weighted mean turns out to be 5.8.

Example 2: Weighted Mean of a Column in a Data Frame

The following code shows how to calculated the weighted mean for a column in a data frame, using another column as the weights:

#create data frame
df <- data.frame(values = c(3, 5, 6, 7, 8),
                 weights = c(.1, .3, .3, .2, .1))

#calculate weighted mean
weighted.mean(x=df$values, w=df$weights)
[1] 5.8

The weighted mean turns out to be 5.8.

Note that you can also calculate the weighted mean for a column in a data frame by using a separate vector as the weights:

#create data frame
df <- data.frame(values = c(3, 5, 6, 7, 8),
                 other_data = c(6, 12, 14, 14, 7),
                 more_data = c(3, 3, 4, 7, 9))

#define vector of weights
weights <- c(.1, .3, .3, .2, .1)

#calculate weighted mean
weighted.mean(x=df$values, w=weights)
[1] 5.8

Once again the weighted mean turns out to be 5.8.

When to Use a Weighted Mean