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Scientific Data Analysis and Statistics using Python
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Europe/Berlin
1.011 (RWTH Aachen)
1.011
RWTH Aachen
Sammelbau der Biologie 2, Worringerweg 3, 52074 Aachen
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Description
In collaboration with the department for Molecular and Systemic Neurophysiology at RWTH Aachen University, we offer an introductory course to statistics. This course combines an overview of basic statistical methods with their application in Python. Participants will learn how to start with their data analysis and interpret their results meaningfully. The course does not require any previous knowledge of statistics. By the end of the course, you will be able to identify appropriate statistical methods, apply them, and interpret your results.
Course Content
1. Data visualisation
2. Parametric and non-parametric tests
3. ANOVA
4. Post-hoc analysis
5. Power analysis
6. Data management and FAIR principles
Methods
- The course will take place face-to-face in Aachen on some of the days during that week that are still to be determined.
- We will use Jupyter Notebooks as interactive computing platform. If you prefer any other Python environment, such as Thonny or Spyder, … you are welcome to use those as well.
Requirements
- Basic skills in programming with Python, such as those taught in our course "Python from Zero to Data Science". In detail, we require basic knowledge using the packages pandas, Matplotlib, Seaborn (not taught in our course but sufficiently similar to Matplotlib), and NumPy.
- You can participate in an introductory face-to-face Python course offered by RWTH Aachen University on 13-16 February 2024 from 10am to 5pm in the same room as the Statistics course. If you are interested, please pre-register for the Python course using the registration form for the statistics course. The exact dates for the course have not yet been specified.
The registration deadline is 26 January 2024. In addition to the three course days on 20-22 February 2024, a tutor will be available on 23 February if you need more time and advise to complete the exercises.
