Degrees of Freedom and Effect Sizes: Crash Course Statistics #28

Today we're going to talk about degrees of freedom - which are the number of independent pieces of information that make up our models. More degrees of freedom typically mean more concrete results. But something that is statistically significant isn't always practically significant. And to measure that, we'll introduce another new concept - effect size. Crash Course is on Patreon! You can support us directly by signing up at   / crashcourse   Thanks to the following Patrons for their generous monthly contributions that help keep Crash Course free for everyone forever: Mark Brouwer, Erika & Alexa Saur, Glenn Elliott, Justin Zingsheim, Jessica Wode, Eric Prestemon, Kathrin Benoit, Tom Trval, Jason Saslow, Nathan Taylor, Divonne Holmes à Court. Brian Thomas Gossett, Khaled El Shalakany, Indika Siriwardena, SR Foxley, Sam Ferguson, Yasenia Cruz, Eric Koslow, Caleb Weeks, Tim Curwick, D.A. Noe, Shawn Arnold, Ruth Perez, Malcolm Callis, Ken Penttinen, Advait Shinde, William McGraw, Andrei Krishkevich, Rachel Bright, Mayumi Maeda, Kathy & Tim Philip, Jirat, Eric Kitchen, Ian Dundore, Chris Peters -- Want to find Crash Course elsewhere on the internet? Facebook -   / youtubecrashcourse   Twitter -   / thecrashcourse   Tumblr -   / thecrashcourse   Support Crash Course on Patreon:   / crashcourse   CC Kids:    / crashcoursekids