| Title | Time | Room | Teacher |
|---|---|---|---|
| Fundamentals of Statistics with Excel | 15.06.2026 09:00 - 16:00 (Mon) | TUM Graduate School: Boltzmannstraße 17, 85748 Garching bei München, Room E003 | Dr. Denis Düsseldorf |
| Fundamentals of Statistics with Excel | 16.06.2026 09:00 - 16:00 (Tue) | TUM Graduate School: Boltzmannstraße 17, 85748 Garching bei München, Room E003 | Dr. Denis Düsseldorf |
This intensive workshop offers a practical introduction to the core principles of statistics, designed specifically for doctoral researchers from all disciplines - no prior knowledge required.
Participants will gain a solid understanding of key statistical methods and learn how to apply them effectively to their own data. The course combines concise theoretical input with hands-on exercises, using Microsoft Excel for the practical component.
- The Role and Relevance of Statistics
- Descriptive Statistics and Data Summarization
- Statistical Charts and Visualizations
- Fundamentals of Probability
- Correlation and Linear Regression
- Introduction to Inferential Statistics
- Hypothesis Testing and Confidence Intervals
- Sampling Methods and Sources of Bias
- Critical Evaluation of Statistical Claims in Scientific Literature
- Common Pitfalls and Errors in Data Analysis
The course alternates between brief theory sessions and hands-on practice, allowing participants to apply concepts immediately using Microsoft Excel. This interactive approach ensures effective learning.
At the beginning of the doctorate │ during the doctorate │ at the end of the doctorate
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A Laptop with Microsoft Excel installed.
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- The trainer was very engaged. Presented the topics in a clear, very intuitive way. Very open to questions. The ones he couldn't immediatly answer, he searched for a solution / answer right away.
- The balance between theoretical and practical sessions was very good
- Very good, clear, and vivid explanations
Dr. Denis Düsseldorf earned his doctoral degree in mathematics from the University of Bonn in 2024 and holds a certification as a 'Data Scientist Specialized in Machine Data Analytics' from the Fraunhofer Research Institute. His doctoral dissertation focused on the numerical resolution of partial differential equations characterized by multi-scale attributes. He works as a freelance consultant specializing in AI, automation, and data analysis, and as a passionate trainer, he teaches programming and mathematical topics to current and aspiring researchers to help them solve practical problems in their research.