Applied statistics can be divided into two areas: **descriptive statistics** and **inferential statistics**.
Descriptive statistics consists of methods for organizing, displaying and describing data by using tables, graphs and summary measures.
In contrast, inferential statistics consists of methods that use sample results to make decisions or predictions about an underlying population (Mann 2012, Weiss 2010).

The word univariate refers to the fact that only one variable is under consideration. The main purpose of univariate statistics is to describe and summarize the data. If two or more variables are analyzed, we refer to bivariate or multivariate analysis or statistics, respectively. In this case we are primarily interested in the relationships between and among a set of variables.

**Citation**

The E-Learning project SOGA-Py was developed at the Department of Earth Sciences by Annette Rudolph, Joachim Krois and Kai Hartmann. You can reach us via mail by soga[at]zedat.fu-berlin.de.

You may use this project freely under the Creative Commons Attribution-ShareAlike 4.0 International License.

Please cite as follow: *Rudolph, A., Krois, J., Hartmann, K. (2023): Statistics and Geodata Analysis
using Python (SOGA-Py). Department of Earth Sciences, Freie Universitaet Berlin.*