Statistical Computing and Programming
Preface
One more robot learns to feel,
Something more than a machine..
The lyrics above are from the song “One More Robot/Sympathy 3000-21”, written by The Flaming Lips in 2002. When I started preparing to teach this course in mid-2023, AI had been around for a year or two already. I was stuck for a long time wondering if this course is still relevant; I played the song quite a few times..
Here’s what I mean: The course is meant to introduce statistics majors (and minors) to three computing languages: R, Python and SAS. But.. why does anyone need to know this when we can just ask Gemini?
If you are taking this course, should you pretend that AI does not exist? Obviously not! If you really need help, don’t hesitate to use AI. But if you do use AI, I would hope that you take some time to dissect it’s solution to aid in more long-term understanding and recall.
I believe there is a need for data analysts to know how to code from scratch, if only because of the value of the process. By coding from nought, and by digging into data ourselves, we sharpen our minds.
In “How to Solve It”, Polya recommends that, upon finding one solution to a problem, we ought to go back and find ways to generalise the solution or to optimise it. Challenging ourselves in these small ways will improve us as data analysts. I hope this course provides you opportunities to do so.
I believe there is great value in struggling with a problem. That’s what university was meant to be about - to allow you to experiment, make mistakes and find your inclinations without too much damage. I sincerely hope you find joy in working with data, R, Python and SAS during this course!
If you are a fellow instructor and you find something useful in this textbook, please do let me know at vik.gopal@nus.edu.sg. The book, along with slides and scripts/notebooks can all be found in the github repository. If you need more details about anything, do feel free to write as well.
So long, and thanks for reading!
Vik