# 7 Skewness and Kurtosis

Skewness and Kurtosis are two different measures of shapes and distribution of a dataset in qualitative methods.

## 7.1 Skewness

Skewness is a measure of the asymmetry of a distribution. It describes the degree to which the distribution deviates from a symmetric shape. A skewness value of 0 indicates a perfectly symmetric distribution. Positive skewness indicates a distribution with a longer tail on the right side, while negative skewness indicates a longer tail on the left side.

## 7.2 Kurtosis

Kurtosis is a measure of the “tailedness” or “peakedness” of a distribution. It describes how the distribution’s tails and peak compare to a normal distribution. A kurtosis value of 0 indicates a distribution with a similar shape to a normal distribution. Positive kurtosis indicates a distribution with heavier tails and a more peaked shape than a normal distribution, while negative kurtosis indicates lighter tails and a less peaked shape.

## 7.3 Generating Skewness and Kurtosis using R

We can use the same `psych`

package to generate skewness and Kurtosis. The `describe()`

function also provides other descriptive statistics, such as mean, median, standard deviation, and range. If you only want to see the skewness and kurtosis, you can use the `skew()`

and `kurtosis()`

functions separately.