Gentle Introductions to Computational and Analytical Methods

This is a collection of resources I developed to provide quick, approachable introductions to computational and analytical methods commonly used in economics, computational social science, computer science, and/or complex systems research. Each resource begins by building intuition for the underlying method before demonstrating its application through a practical example in Python. The goal is to offer an accessible starting point for students, researchers, and analysts who want to begin applying these tools in their own work.

Causal Inference Methods:

CI1 - Sharp Regression Discontinuity designs
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Nonparametric Methods:

NP1 - Kernel Density Estimation
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Classical Machine Learning:

ML1 - Nearest Centroid and K-Nearest Neighbors
ML2 - Naive Bayes
ML3 - Decision Trees and Random Forests
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