Channel: Brandon Foltz

Category: Education

Tags: akaike information criterion explainedstatistics 101 multiple regressionaiccakaike information criterion (aic)bayesian information criterionlinear regressionbest subsets regressionmallows cpstatistics 101: multiple regressionbrandon foltz multiple regressionmachine learningakaike information criterionstatistics 101statistics 101 regressionbrandon foltz statistics 101regressionaicmultiple regressionbicbrandon foltzmultiple linear regression

Description: In this Statistics 101 video, we explore the regression model analysis scores known as AIC, AICc, and BIC which are acronyms for Akaike Information Criterion and Bayesian Information Criterion. This is done through conceptual explanations, finding the value by hand, and by analyzing computer output from JMP. Enjoy! My playlist table of contents can be found here: bcfoltz.com/blog/stats-101 You can also find Video Companion Guide PDFs here: bcfoltz.com/blog JMP by SAS: jmp.com/en_us/software.html Maximum Likelihood @StatQuest with Josh Starmer youtube.com/watch?v=XepXtl9YKwc Happy learning! #statistics #machinelearning #datascience