# Calculate Kurtosis in R

## Your goal

You need to calculate the kurtosis of a numerical dataset in R.

## Step-by-step tutorial

We'll use the `moments`

package for this. Install it as follows:

`> install.packages("moments")`

The `moments`

package supports a couple of different kurtosis calculations, both involving
estimating kurtosis from samples. One is an estimator for Pearson's (non-excess) kurtosis by way of the
`kurtosis`

function. The other is an estimator for Geary's kurtosis using the `geary`

function. Here we'll use `kurtosis`

.

For data, let's use the Titanic dataset. You
can use readr's read_csv function to read the file. We'll
calculate the skewness of the `age` column. Note that in the original dataset this variable has some
`?`

values, so it reads as character data. We need to remove those and convert the column to
numeric data.

```
> library(moments)
> library(readr)
> titanic <- read_csv("titanic-full.csv")
> age <- as.numeric(titanic$age)
> kurtosis(age, na.rm=TRUE)
```

We use `na.rm=TRUE`

to remove NAs from the data. Alternatively, we could have used
`age <- na.omit(as.numeric(titanic$age))`

to remove them.

The result is 3.144524.

For visualization, we can generate a histogram using `hist`

as well: