Research School for Socio-Economic and
Natural Sciences of the Environment
Research School for Socio-Economic and
Natural Sciences of the Environment

Introduction to Probability and Applied Statistics using Python

Date: 13 May 2019 - 15 May 2019
Location: UFZ Leipzig, Germany

The course uses a combination of lectures and participatory activities to understand the principles of statistical inference. It will answer questions such as: “Why do I need statistics?”, “What’s in a p-value?”, “How many replicates do I need”, and hopefully help avoid questions such as “Are my 5 years of data useless?”

The course will cover all steps of statistical inference: data acquisition, basic statistical analyses, and basic graphs. A large portion of the course will be dedicated to practical exercises using the language Python. The course will also include instruction on the use of Python along every step of the process. At the end of the course, participants will have the opportunity to do a project with their own data (or freely available data).

Didactic Aims

Understand probability and probability distributions; the ability to perform and interpret descriptive statistics; to use and interpret basic statistical tests; to use and interpret (Ordinary Least Squares) linear regression and to understand the difference between classical and Bayesian statistics.

Didactic Elements

Practical exercises (mostly writing code), lectures, discussions

Target Group

  • Doctoral Researchers
  • Postdocs & Senior Scientists
  • Technical Staff

Required Prior Knowledge

Basic knowledge of Computer Science, i.e., at least one programming language (not necessarily Python) is required. No previous knowledge of statistics is required.

> More information about this course

> More UFZ courses

Registration and fee

Participation fees do not apply to cooperation partners, i.e. PhD candidates of SENSE partner WIMEK.
The current conditions of participation and use apply.
Please note: In order to register, a personal account has to be created first.

Search course

Follow this link to search for interesting courses!