Applied Data Analysis

Applied statistics for people who will end up writing the analysis code, not just reading the output: you learn the reasoning behind descriptive measures, sampling, hypothesis tests, correlation and regression, and you implement each one in R as you go. The weekly lab sessions are where most of the work lives — quizzes, a lab exam, and a term project push you to actually prepare messy data with dplyr, visualize it with ggplot, and defend the test you chose. It assumes no prior stats background and acts as the bridge between your earlier programming courses and any later work in data mining, ML, or undergrad research where "what does this number mean" matters more than running the function.