Inferential statistics consists of methods that use sample results to make decisions or predictions about a population (Mann 2012, Weiss 2010). This area of applied statistics is fundamental in all situations, in which the knowledge about the population is limited or even missing at all, which is the case in most real-life applications. In addition, in many cases it is just too expensive, very time consuming or virtually impossible to collect data on every member of a population. Therefore, a sample is taken from the population and an appropriate sample statistic is calculated. Then, based on the value of the sample statistic, a value is assigned to the corresponding (unknown) population parameter.

This procedure, by which a numerical value is assigned to a population parameter based on the information collected from a sample is called estimation. The numerical value is called an estimate of the population parameter. The sample statistic used to estimate a population parameter is called an estimator (Mann 2012).

**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.*