new edition of my remixed data science textbook

I’m happy to share that the Fall 2023 edition of my remixed Introduction to Data Science textbook is now available on my website. This book adapts material from the “ModernDive” Statistical Inference via Data Science course, Catherine D’Ignazio and Lauren Klein’s excellent Data Feminism, a number of other Creative Commons-licensed works, and some of my own contributions to put together a no-cost, openly-licensed textbook for my data science students. I put together the first edition of this book for last Fall’s version of this course, but the first run through taught me a lot, and I’m very happy about this edition (though I do have a small laundry list of errors to fix, and I’d like to eventually get into some fiddlier bits like removing social media icons from the header).

Last year’s version was available through Royce Kimmons’s EdTechBooks platform, but as much as I love Royce’s work there, it became apparent early on that it wasn’t a good fit for the material that I was working on. I spent a bunch of time this summer migrating the textbook to a version that’s put together through the bookdown package for R and hosted on my website. Since I was remixing much of my material from the ModernDive book (which is already in bookdown), this isn’t as much work as it could have been—besides, bookdown has the advantage (and raison d’être, for that matter) of integrating R code and text much more closely than I could ever have done on EdTechBooks. A year ago, I wasn’t sure that I could handle doing this project in bookdown, but even though I still have a lot to learn, I’m very, very happy with this approach.

I don’t know that this is the best data science textbook in the world, and nearly everything that is good about it is borrowed from other sources, but I’m glad that students don’t have to pay for an outdated textbook anymore (like they did when I first took over this course), that I’ve picked up some skills along the way, and that I’ve been able to put together a textbook that fits how I want to teach data science to my students. This has gotten me more excited about OER than I’ve been in a long time, and I’m hoping to push some more support for these kinds of efforts in my unit and college.

• macro
• Work
• ICT 661
• OER
• teaching
• Creative Commons
• bookdown
• R
• open textbooks
• alternative textbooks