Embark on a comprehensive statistical journey through this extensive lecture series spanning over 25 hours. Delve into advanced statistical concepts, starting with the foundational "Golem of Prague" and progressing through diverse topics such as forking data, geocentric models, categories and curves, confounds, and controls. Master Markov Chain Monte Carlo techniques, explore event modeling, and tackle hidden confounds in count data. Advance to multilevel models, correlated features, and social network analysis. Gain insights into Gaussian processes, measurement issues, missing data handling, and generalized linear models. Conclude with a unique perspective on statistical applications in unexpected areas, challenging conventional thinking about data analysis and interpretation.
Overview
Syllabus
Statistical Rethinking 2023 - 01 - The Golem of Prague
Statistical Rethinking 2023 - 02 - The Garden of Forking Data
Statistical Rethinking 2023 - 03 - Geocentric Models
Statistical Rethinking 2023 - 04 - Categories & Curves
Statistical Rethinking 2023 - 05 - Elemental Confounds
Statistical Rethinking 2023 - 06 - Good & Bad Controls
Statistical Rethinking 2023 - 07 - Fitting Over & Under
Statistical Rethinking 2023 - 08 - Markov Chain Monte Carlo
Statistical Rethinking 2023 - 09 - Modeling Events
Statistical Rethinking 2023 - 10 - Counts & Hidden Confounds
Statistical Rethinking 2023 - 11 - Ordered Categories
Statistical Rethinking 2023 - 12 - Multilevel Models
Statistical Rethinking 2023 - 13 - Multilevel Adventures
Statistical Rethinking 2023 - 14 - Correlated Features
Statistical Rethinking 2023 - 15 - Social Networks
Statistical Rethinking 2023 - 16 - Gaussian Processes
Statistical Rethinking 2023 - 17 - Measurement & Misclassification
Statistical Rethinking 2023 - 18 - Missing Data
Statistical Rethinking 2023 - 19 - Generalized Linear Madness
Statistical Rethinking 2023 - 20 - Horoscopes
Taught by
Richard McElreath
