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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).
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.
Practical exercises (mostly writing code), lectures, discussions
Basic knowledge of Computer Science, i.e., at least one programming language (not necessarily Python) is required. No previous knowledge of statistics is required.
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.