Today we're going to wrap up our discussion of General Linear Models (or GLMs) by taking a closer looking at two final common models: ANCOVA (Analysis of Covariance) and RMA (Repeated Measures ANOVA). We'll show you how additional variables, known has covariates can be used to reduce error, and show you how to tell if there's a difference between 2 or more groups or conditions. Between Regression, ANOVA, ANCOVA, and RMA you should have the tools necessary to better analyze both categorical and continuous data. Crash Course is on Patreon! You can support us directly by signing up at Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Mark Brouwer, Kenneth F Penttinen, Trevin Beattie, Satya Ridhima Parvathaneni, Erika & Alexa Saur, Glenn Elliott, Justin Zingsheim, Jessica Wode, Eric Prestemon, Kathrin Benoit, Tom Trval, Jason Saslow, Nathan Taylor, Brian Thomas Gossett, Khaled El Shalakany, Indika Siriwardena, SR Foxley, Sam Ferguson, Yasenia Cruz, Eric Koslow, Caleb Weeks, D.A. Noe, Shawn Arnold, Malcolm Callis, Advait Shinde, William McGraw, Andrei Krishkevich, Rachel Bright, Mayumi Maeda, Kathy & Tim Philip, Jirat, Ian Dundore -- Want to find Crash Course elsewhere on the internet? Facebook - Twitter - Tumblr - Support Crash Course on Patreon: CC Kids: