Springe direkt zu Inhalt

Multivariate approaches

Welcome to the section Multivariate Approaches. In this section we explore the the vast field of geodata and spatial data analysis. In the following subsections we present the statistical theory and we provide hands-on coding recipes in the Python programming language. If you are not yet comfortable with Python it is recommended to go through the section Introduction to the statistical programming language Python first.

Please note that the content of the section Multivariate Approaches complements and extends the material covered in the section Basic of Statistics.

Every effort has been made in the preparation of this section to ensure the accuracy of the information presented. However, the information given comes without warranty, either express or implied. Neither the author, nor Freie Universitaet Berlin will be held liable for any damages caused or alleged to be caused directly or indirectly by the content of this section.

If you find any writing or coding errors or have any suggestions to improve the readability we would appreciate if you contact us via soga[at]zedat.fu-berlin.de.


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.

Creative Commons License
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.