Stats 2: Comparing Groups & Relationships
Three teaching methods, one exam. Two questionnaire scores that seem to rise together. Research gets interesting once you compare more than two things at once, and this course is where the classic tests live: ANOVA in its one-way, factorial and repeated-measures forms, chi-square for counts, correlation and regression for relationships.
It picks up where Stats 1 stops. You should be comfortable with sampling distributions, t-tests and what a p-value means; everything else is built here. Assumption checking gets full lessons rather than a footnote, because knowing when a test's guarantees hold is the difference between running an analysis and understanding one. The rank-based alternatives are covered too, for the days your data refuse to behave.
These ten lessons cover most of what an undergraduate methods course grades you on. Afterwards, Stats 3 takes regression from one predictor to many. One Study, Start to Finish puts this course's factorial ANOVA inside a whole project, from the research question to the write-up.