Resources

Further readings if you’d like to deepen your knowledge and skill after the workshop:

Ismay, C., & Kim, A. Y. (2024). Statistical inference via data science. https://moderndive.com/

This book offers a gentle introduction to R, while also covering foundational research methods such as sampling, hypothesis testing, and making inferences. I really like how it combines both programming and research basics; very suitable for beginners!

Wickham, H., Çetinkaya-Rundel, M., & Garrett Grolemund. (2024). R for data science (2e) (2nd ed.). https://r4ds.hadley.nz/

A great book for R beginners! It introduces the popular tidyverse package and explains how to make the most of it. It also offers useful tips for managing projects and outlines recommended steps for transforming raw data into meaningful insights and discoveries.

Wilke, C. O. (2024). Fundamentals of data visualization. https://clauswilke.com/dataviz/

I noticed that some of you are particularly interested in visualizations. While I couldn’t cover more of this topic during the workshops, if you’re eager to dive deeper, this book does a great job of covering foundational theories that I believe are both important and helpful.