Though I'm a psychometrician/statistician in my job, I've been dipping my toe into the pool of data science, so I've blogged about data science and the related topics. In fact, one such post resulted in a lively discussion on Facebook about what data science is exactly.
I mostly remained a voyeur to this discussion. I don't see anything wrong with stepping back and listening to what others think, rather than always jumping in with my opinion.
But, I've still committed a sin in that I've used terms like data science, machine learning, and artificial intelligence in rather unclear, even sloppy ways. Fortunately, David Robinson of Variance Explained is here to save the day! So in lieu of my own statistical sins posts for the day, I'm calling myself out and recommending you read David's awesome post on the difference among these three terms.
As for me, I'm working on pulling together a dataset on reading habits of my Goodreads friends from 2017 - a dataset I started on a sleepless night earlier this week. I'm just about ready to start analyzing it. Stay tuned for some fun analyses! (But one thing I've already learned is that the most read book among my friends in 2017 was The Handmaid's Tale.)