BiteSize Statistics for Intermediate Learners

BiteSize Statistics for Business: Correlation and Regression Analysis is the third and final course in the BiteSize Stats for Business specialization. It moves from testing whether two groups differ to modeling how two or more variables relate — quantifying association, fitting a predictive line, and rigorously checking whether that line can be trusted. Across five modules, learners progress from scatterplots and the Pearson correlation coefficient (with significance testing and common pitfalls), through simple linear regression and OLS estimation, to inference for the regression slope, model-fit diagnostics (R², residual plots, influential points), and finally multiple regression with multicollinearity checks. Every core lesson pairs a focused reading with a hands-on interactive notebook built around a realistic business scenario, and every module includes a fully worked demo case study and one or more student-led practice projects applying the module's tools to a new dataset.

BiteSize Statistics for Business: Hypothesis Testing for Single Samples is the first course in the BiteSize Stats for Business specialization. It moves from probability theory to inferential statistics: given one sample, how do you rigorously test a claim about the population it came from — and how confident should you be in the answer? Across five modules, learners progress from the logic of hypothesis testing (hypotheses, error types, p-values, decision rules), through one-sample Z-tests and t-tests for means and proportions with their matching confidence intervals, to the chi-square goodness-of-fit test for categorical data, and finally statistical power, effect size, and sample size planning. Every core lesson pairs a focused reading with a hands-on interactive notebook built around a realistic business scenario, and every module includes a fully worked demo case study and an ungraded practice project applying the module's tools to a new scenario.