Learning Tracks

A learning track is a curated sequence of resource pages that builds up knowledge or skill on a topic in a deliberate order. Unlike the Resource Library, which is organized for browsing, learning tracks are organized for learning — each page in a track builds on the ones before it.

Learning tracks are written as general learning paths, not course companions. They are useful if you want to develop competence in an area rather than look up a single reference.

Photo by Roland Denes on Unsplash.

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Available learning tracks

Getting started

• Getting Started with R — installation, the RStudio interface, core object types, and project setup; no prior experience required
• A Recap of Undergraduate Statistics — conceptual foundations, data types, descriptive statistics, probability theory, and inference

Applied data work (BA)

• Data Workflow in R — importing data, cleaning with the tidyverse, visualising with ggplot2, and documenting in Quarto
• Introduction to Regression in R — logarithms, linear regression with lm(), diagnostics, categorical predictors, and interaction terms
• Measuring Development — why observation is theory-laden, gathering cross-country data in R, and what the major families of development indicators do and do not capture

Advanced methods (MA)

• Regression and Causal Inference — logistic regression, DAGs, panel fixed effects, and publication-ready figures