To calculate the mean of a set of data in R, you can use the `mean()`

function. This function takes a numeric vector as an argument and returns the mean of the values in the vector.

Here is an example of how to use the `mean()`

function to calculate the mean of a vector of numbers:

```
# Create a vector of numbers
x <- c(1, 2, 3, 4, 5)
# Calculate the mean of the vector
mean(x)
```

The `mean()`

function will return the result `3`

, which is the mean of the values in the vector `x`

.

You can also use the `mean()`

function to calculate the mean of a column of a data frame. For example:

```
# Load a data frame
data <- read.csv("data.csv")
# Calculate the mean of a column in the data frame
mean(data$column_name)
```

This will calculate the mean of the values in the `column_name`

column of the data frame `data`

.

Note that the `mean()`

function will ignore any missing or NA values in the data. If you want to include missing values in the calculation, you can use the `na.rm = FALSE`

argument:

```
mean(x, na.rm = FALSE)
```

This will include missing values in the calculation of the mean.

Overall, the `mean()`

function is a simple and effective way to calculate the mean of a set of data in R.