🗓️ Week 02 - Computational Thinking and Reproducibility

This week will introduce students to how to think computationally, data structures, and project workflow (linking R projects to GitHub), focusing on reproducibility. Students will also be shown how to load and update relevant data science libraries into R.

👨‍🏫 Lecture Slides

Either click on the slide area below or click here to view it in fullscreen. Use your keypad to navigate the slides.

🎥 Looking for lecture recordings? You can only find those on Moodle.

✍️ Lab Materials

🚧 Students will create an RStudio project with a solid workflow, while practicing the principles of reproducibility.🚧

📚 Required Reading

• Christensen, G., Freese, J., & Miguel, E. (2019). Transparent and Reproducible Social Science Research: How to Do Open Science. University of California Press. (Chapter 10 & 11).

• Wickham, H., Çetinkaya-Rundel, M., & Grolemund, G. (2023). R for data science. ” O’Reilly Media, Inc.”. (Chapter 7).