Course materials

Textbooks

All books are freely available online:

  1. 📘 [ims]: Mine Çetinkaya-Rundel and Jo Hardin (2024): Introduction to Modern Statistics, 2e, OpenIntro;
  2. 📗 [r4ds]: Hadley Wickham, Mine Çetinkaya-Rundel, and Garrett Grolemund (2022): R for Data Science, 2e, O’Reilly.

ims is the main course text, and it is supported by extra resources that you may find helpful:

  • 🎥 Video lectures: Dr. Çetinkaya-Rundel is a member of our department, and she has recorded companion videos for many of the course topics. Sometimes these may venture deeper into R coding than is necessary for 101, but you’ll quickly learn to tune out what you don’t need;
  • 🏋️ Tutorials: every section of the book comes with an interactive tutorial that walks you through the coding skills necessary to execute the ideas.

You are not required to use these, but they are available if you seek extra practice, alternative instruction, or want to get a head start before lecture. As we go along I will link to the relevant stuff in the MORE section of our course schedule.

Note

Our course (the lectures, labs, and homeworks) is meant to be self-contained. As I said, these tutorials and videos are just optional practice. And in particular, if you encounter new ideas in the tutorials or videos that are not introduced anywhere else in the course materials, then you are not responsible for knowing these things on an exam.

Technology

You will need to bring a laptop to all lectures and labs. Options for obtaining a laptop through the university are described here. Armed with your trusty laptop, you must be able to access the following:

If access to technology becomes a concern for you during the semester, contact the instructor immediately to discuss options.