Statistics - Describing Data
Describing data is typically the second step of statistical analysis after gathering data.
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 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:
- Mean, median and mode
- Range and interquartile range
- Quartiles and percentiles
- Standard deviation and variance
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.