Rodolfo Lourenzutti
Department of Statistics · University of British Columbia
I am an instructor in the Department of Statistics at the University of British Columbia (UBC).
My work focuses on teaching undergraduate statistics and data science. I am particularly interested in developing interactive learning materials that allow students to explore statistical concepts. I want to make statistics more accessible and engaging for students, and I believe that interactive materials can help achieve this goal.
Recently, I have shifted my work toward closing the gap between statistical theory and practice, with a focus on applied statistics and data science. I am interested in developing materials that help to prepare fresh graduate students for jobs in industry.
Courses & Teaching
Some of my course materials are available online. You can find lecture slides, notes, and other resources for the courses I teach below. I’m still transitioning these materials to online formats, so please check back for updates.
STAT 201
Statistical Inference
Resampling, permutation tests, bootstrapping, confidence intervals, and hypothesis testing.
STAT 200
Elementary Statistics
Data exploration, study design, probability foundations, sampling distributions, and estimation.
STAT 306
Relationships in Data
Simple and multiple linear regression, model selection, diagnostics, and generalized linear models.
Interactive Notes & Singletons
In addition to lecture slides, I write interactive notes and standalone tutorials:
- STAT 201 Lecture Notes Book: An online textbook covering statistical inference with embedded exercises that run in-browser. (Under development)
- Singletons: Standalone explorations of specific topics, including:
- A/B Testing Walkthrough: Formulating hypotheses, randomization, and multiple testing.
- Feedforward Neural Networks: An introduction to multilayer perceptrons and backpropagation.
- R Playground for Exams: A lightweight, sandboxed in-browser scratchpad for students.
Interests
- Statistical Pedagogy: Active learning, reproducible workflows, and computational thinking in introductory courses.
- Interactive Computing: Using WebAssembly (WebR) and Quarto for live document execution without server setups.
- Applied Statistics: Resampling methods, non-parametric inference, and regression modeling.