# Summary statistics

In descriptive statistics, **summary statistics** are used to summarize a set of observations, in order to communicate as much as possible as simply as possible. Statisticians commonly try to describe the observations in

- a measure of location, or central tendency, such as the arithmetic mean, median, mode, or interquartile mean
- a measure of statistical dispersion like the standard deviation, variance, range, or interquartile range, or absolute deviation.
- a measure of the shape of the distribution like skewness or kurtosis

The Gini coefficient was originally developed to measure income inequality, but can be used for other purposes as well.

## Example

The following example using R is the standard summary statistics of a randomly sampled normal distribution, with a mean of 0, standard deviation of 1, and a population of 50:

> x <- rnorm(n=50, mean=0, sd=1) > summary(x) Min. 1st Qu. Median Mean 3rd Qu. Max. -1.72700 -0.49650 -0.05157 0.07981 0.67640 2.46700