Journal 42
May 20 - May 26 This course is absolutely flying by. After a bit of research and practice, I finally am really getting the hang of using Google Colab, and I am thoroughly enjoying creating and editing the various graphs. This week's work focused on probability distributions, relationships between variables, and data visualization. I learned a lot about the difference between joint, marginal, and conditional probabilities. At first some of the notation was confusing such as deciding when to use P(A|B) or P(A and B). However, after working through the notes and homework, I started to understand that conditional probability is really about narrowing the dataset to a specific group first and then measuring probabilities within that group. The crosstab examples using normalize='index' and normalize='columns' helped to clarify this idea because I could visually see how the probabilities changed depending on which variable was being conditioned on. We also spent time lea...