I always knew Principal Component Analysis (PCA) as a dimensionality reduction technique. Way too many features? PCA. Need to visualize clustering? PCA. Exploratory data analysis? PCA. It’s definitely one of my go-to analysis back then, but not because of its usefulness—it was one of the few tools I knew existed, so might as well, I […]

During my early days of learning statistics, I encountered a pretty interesting phenomenon while reading a (relatively) ancient article. The story goes like this: In the fall of 1973, a study on gender bias among graduate school admissions to University of California, Berkeley made headlines. The reason for this was that the admission figures showed […]

Back in university, my genetics professor introduced the concept of chi-square tests like it was a magical instrument. Before I was ever interested in any statistics, I always had a script from the lecture notes that ran some code on R, and all I had to do was reject either the hypothesis that my two […]