Tutorials
Open-source R tutorials for quantitative methods
A series of original tutorials I developed for CU Boulder’s PSCI 2075 (Quantitative Methods). They’re designed for students with no prior coding experience, with a focus on building intuition before syntax. Free to use, share, and remix.
The series
1. Greek Notation & Descriptive Stats
Build the bridge from formal notation (Σ, μ, σ) to R code. Means, variance, and standard deviation from first principles. R Intro
Open tutorial →
2. The Pipe Operator
The single most important readability trick in modern R. Why %>% and |> exist and when to use each. R tidyverse
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3. Group, Filter, Mutate, Plot
The everyday verbs of data manipulation in dplyr, with ggplot2 to visualize the results. R dplyr ggplot2
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4. Variable Transformations
Distributions, log transforms, and recoding — when to reach for each, and what they do to your inferences. R Stats
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5. Using AI Chatbots to Learn R
Strategies for productive LLM-assisted coding without short-circuiting your own learning. R LLMs Pedagogy
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6. File Systems & Working Directories
The single biggest source of “it works on my machine” pain. Paths, projects, and here::here(). R RStudio
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Sample syllabi
- INTD 1027 — The Study of Post-War Fascism (Middlebury College)
- PSCI 2075 — Study Guide (CU Boulder)
Feedback
Spotted an error? Have a suggestion? Email me — I update these every term.