You Know I’m All About that Bayes: Crash Course Statistics #24
Today we’re going to talk about Bayes Theorem and Bayesian hypothesis testing. Bayesian methods like these are different from how we've been approaching statistics so far, because they allow us to update our beliefs as we gather new information - which is how we tend to think naturally about the world. And this can be a really powerful tool, since it allows us to incorporate both scientifically rigorous data AND our previous biases into our evolving opinions.
CORRECTION: At 2:09 the righthand side of the equation should not have P()'s, it should just be the raw numbers.
Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/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, 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 - http://www.facebook.com/YouTubeCrashCourse
Twitter - http://www.twitter.com/TheCrashCourse
Tumblr - http://thecrashcourse.tumblr.com
Support Crash Course on Patreon: http://patreon.com/crashcourse
CC Kids: http://www.youtube.com/crashcoursekids
Видео You Know I’m All About that Bayes: Crash Course Statistics #24 канала CrashCourse
CORRECTION: At 2:09 the righthand side of the equation should not have P()'s, it should just be the raw numbers.
Crash Course is on Patreon! You can support us directly by signing up at http://www.patreon.com/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, 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 - http://www.facebook.com/YouTubeCrashCourse
Twitter - http://www.twitter.com/TheCrashCourse
Tumblr - http://thecrashcourse.tumblr.com
Support Crash Course on Patreon: http://patreon.com/crashcourse
CC Kids: http://www.youtube.com/crashcoursekids
Видео You Know I’m All About that Bayes: Crash Course Statistics #24 канала CrashCourse
Показать
Комментарии отсутствуют
Информация о видео
Другие видео канала
Bayes in Science and Everyday Life: Crash Course Statistics #25StatQuest: Probability vs LikelihoodAll About that Bayes: Probability, Statistics, and the Quest to Quantify UncertaintyChi-Square Tests: Crash Course Statistics #29But what is a Neural Network? | Deep learning, chapter 1Conditional Probability, part 1 128-1.8.aIntroduction to Bayesian data analysis - part 1: What is Bayes?5 tips to improve your critical thinking - Samantha AgoosRegression: Crash Course Statistics #32A friendly introduction to Bayes Theorem and Hidden Markov ModelsBayes theoremThe Shape of Data: Distributions: Crash Course Statistics #7What is Engineering?: Crash Course Engineering #1Regression to the Mean17 Probabilistic Graphical Models and Bayesian Networks17. Bayesian StatisticsA visual guide to Bayesian thinkingHow P-Values Help Us Test Hypotheses: Crash Course Statistics #21The Bayesian TrapHow Bayes Theorem works