# Statistics - Describing Data

Describing data is typically the second step of statistical analysis after gathering data.

## Descriptive Statistics

The information (data) from your sample or population can be visualized with graphs or summarized by numbers. This will show key information in a simpler way than just looking at raw data. It can help us understand how the data is distributed.

Graphs can visually show the data distribution.

Examples of graphs include:

Some graphs have a close connection to numerical summary statistics. Calculating those gives us the basis of these graphs.

For example, a box plot visually shows the quartiles of a data distribution.

Quartiles are the data split into four equal size parts, or quarters. A quartile is one type of summary statistics.

### Summary statistics

Summary statistics take a large amount of information and sums it up in a few key values.

Numbers are calculated from the data which also describe the shape of the distributions. These are individual 'statistics'.

Some important examples are:

Note: Descriptive statistics is often presented as a part of statistical analysis.

Descriptive statistics is also useful for guiding further analysis, giving insight into the data, and finding what is worth investigating more closely.

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