Introduction to Data Analysis and R: Descriptive Statistics

Descriptive stats are one of the most basic types of analyses. They are often conducted before any inferential analysis and are included with other results of a particular study. Descriptive stats are are meant to describe and summarize data, with the goal of revealing important patterns that are not readily apparent when looking at the raw data as a whole. Because they are used to help determine the general characteristics of your variables and underlying data, the concept of statistical significance does not apply to descriptive stats.

Following the general theme of this module, descriptive stats generally fall into three main groups:

1. Measures of proportion
2. Measures of centrality
3. Measures of dispersion

Several of the following pages contain equations for some of the measures we will be talking about. You do not need to try to memorize the equations, but you will need to understand them, as they are important for understanding many of the comparatively more complex inferential statistical analyses.