Teaching

I teach applied statistics and quantitative methods for decision-making at the undergraduate level. My approach emphasizes building intuition before formalism: students work with real datasets from the outset, learn to formulate testable hypotheses, and develop the ability to interpret statistical evidence critically. I use a combination of lecture slides, hands-on R workshops, and applied exercises drawn from business and policy contexts.

Estadística para la Toma de Decisiones

Universidad Icesi, Cali Business Analytics Program (Undergraduate) 2025–present

This course introduces probability, statistical inference, and hypothesis testing as tools for evidence-based decision-making in business and policy contexts. Students learn to move from descriptive summaries to causal questions, working with real-world datasets in R.

Probability & distributions Estimation & confidence intervals Hypothesis testing Simple & multiple regression Applied R workshops

Introduction to Counterfactual Impact Evaluation

Alliance of Bioversity International and CIAT Professional training for researchers 2023

A training module designed for CGIAR researchers on when to use impact evaluation, which methods fit different contexts, and what data requirements each approach demands. Covers the logic of counterfactuals, randomized controlled trials, difference-in-differences, and propensity score matching.

Training materials (CGSpace) →