https://github.com/rmcelreath/stat_rethinking_2024 Skip to content Navigation Menu Toggle navigation Sign in * Product + GitHub Copilot Write better code with AI + Security Find and fix vulnerabilities + Actions Automate any workflow + Codespaces Instant dev environments + Issues Plan and track work + Code Review Manage code changes + Discussions Collaborate outside of code + Code Search Find more, search less Explore + All features + Documentation + GitHub Skills + Blog * Solutions By company size + Enterprises + Small and medium teams + Startups By use case + DevSecOps + DevOps + CI/CD + View all use cases By industry + Healthcare + Financial services + Manufacturing + Government + View all industries View all solutions * Resources Topics + AI + DevOps + Security + Software Development + View all Explore + Learning Pathways + White papers, Ebooks, Webinars + Customer Stories + Partners * Open Source + GitHub Sponsors Fund open source developers + The ReadME Project GitHub community articles Repositories + Topics + Trending + Collections * Enterprise + Enterprise platform AI-powered developer platform Available add-ons + Advanced Security Enterprise-grade security features + GitHub Copilot Enterprise-grade AI features + Premium Support Enterprise-grade 24/7 support * Pricing Search or jump to... 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Dismiss alert {{ message }} rmcelreath / stat_rethinking_2024 Public * Notifications You must be signed in to change notification settings * Fork 119 * Star 1k License CC0-1.0 license 1k stars 119 forks Branches Tags Activity Star Notifications You must be signed in to change notification settings * Code * Issues 2 * Pull requests 0 * Projects 0 * Security * Insights Additional navigation options * Code * Issues * Pull requests * Projects * Security * Insights rmcelreath/stat_rethinking_2024 main BranchesTags [ ] Go to file Code Folders and files Name Name Last commit message Last commit date Latest commit History 92 Commits homework homework memes memes scripts scripts slides slides LICENSE LICENSE README.md README.md title.gif title.gif View all files Repository files navigation * README * CC0-1.0 license Statistical Rethinking (2024 Edition) Instructor: Richard McElreath Lectures: Uploaded and pre-recorded, two per week Discussion: Online (Zoom), Fridays 3pm-4pm Central European (Berlin) Time Purpose This course teaches data analysis, but it focuses on scientific models. The unfortunate truth about data is that nothing much can be done with it, until we say what caused it. We will prioritize conceptual, causal models and precise questions about those models. We will use Bayesian data analysis to connect scientific models to evidence. And we will learn powerful computational tools for coping with high-dimension, imperfect data of the kind that biologists and social scientists face. Format Online, flipped instruction. I will pre-record the lectures each week. We'll meet online once a week for an hour to discuss the material. The discussion time (3-4pm Berlin Time) should allow people in the Americas to join in their morning. We'll use the 2nd edition of my book, , and possibly some draft chapters for the 3rd edition. I'll provide a PDF of the book to enrolled students. Registration: Registration hit the cap of 200 already and the wait list is also full. So registration is closed for this year. If people drop or stop attending discussions, I will invite from the wait list. - Calendar & Topical Outline There are 10 weeks of instruction. Links to lecture recordings will appear in this table. Weekly problem sets are assigned on Fridays and due the next Friday, when we discuss the solutions in the weekly online meeting. Full lecture playlist: Note about slides: In some browsers, the slides don't show correctly. If points are missing from plots, download the slides PDF instead of viewing in browser. Week # Meeting Reading Lectures # date [1] < Week 05 January Chapters 1, 2 Slides> 01 and 3 [2] < Slides> Week [3] 02 12 January Chapter 4 [4] < Slides> Week [5] 03 19 January Chapters 5 and 6 [6] < Slides> Week 26 January Chapters 7,8,9 [7] 04 [8] Week 02 Chapters 10 and [9] 05 February 11 [10] < Slides> Week 09 Chapters 11 and [11] 06 February 12 [12] [13] < Week 16 Chapter 13 Slides> 07 February [14] Week 23 Chapter 14 [15] 08 February [16] Week 01 March Chapter 15 [17] 09 [18] Week Chapters 16 and [19] 10 08 March 17 [20] Coding This course involves a lot of scripting. Students can engage with the material using either the original R code examples or one of several conversions to other computing environments. The conversions are not always exact, but they are rather complete. Each option is listed below. Original R Flavor For those who want to use the original R code examples in the print book, you need to install the rethinking R package. The code is all on github https://github.com/rmcelreath/rethinking/ and there are additional details about the package there, including information about using the more-up-to-date cmdstanr instead of rstan as the underlying MCMC engine. R + Tidyverse + ggplot2 + brms The conversion is very high quality and complete through Chapter 14. Python and PyMC3 The conversion is quite complete. Julia and Turing The conversion is not as complete, but is growing fast and presents the Rethinking examples in multiple Julia engines, including the great . Other The are several other conversions. See the full list at https:// xcelab.net/rm/statistical-rethinking/. Homework and solutions I will also post problem sets and solutions. Check the folders at the top of the repository. About No description, website, or topics provided. 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