I am an early-career researcher and data scientist who loves solving puzzles, figuring things out, and modeling our crazy world. I'm passionate about teaching and spreading the joy of statistics.
At the University of Economics in Prague, I study Bayesian approaches to causality and statistical inference. I am fond of methods like Directed Acyclic Graphs (DAGs), General Linear Models (GLMs), hierarchical models, state–space models, and sampling methods.
I am eager to use statistics to push the limits of science even further. If you need someone to collaborate with, I would be happy to work with you. Just
I design and deliver university courses and professional workshops on various topics (statistics, data analyst, machine learning) in various tools (R, Python, Excel, Shiny). If you feel like I could help you with your thesis, data analysis, statistical work, or you just need help clarifying something, don't hesitate to
Databon materials may be outdated, as I no longer work with that organization. But feel free to check out how I work!
Selected excerpts from student feedback and course evaluations (tutoring listed on doucuji.eu), and teaching engagements at Coders Lab and Data Academy.
When it comes to statistical analysis, unbiased estimators play a critical role in obtaining accurate results. But what exactly is an unbiased estimator, and how can it be applied in practical situations?
Consistent estimators hold a pivotal role in delivering precise statistical outcomes. Let's unravel their mystery and reveal how they shape real-world prediction scenarios.
