rmcelreath/stat_rethinking_2022
Stat Rethinking 2022
Este proyecto es una colección de cursos y recursos educativos de estadística bayesiana. Proporciona materiales de instrucción, conjuntos de problemas y soluciones diseñados para aprender análisis de datos bayesianos y modelado causal.
El repositorio incluye una suite de scripts de visualización de datos estadísticos utilizados para generar animaciones y gráficos instructivos. También contiene ejemplos de código que implementan modelado bayesiano y análisis de supervivencia a través de múltiples lenguajes de programación para demostrar diferentes enfoques computacionales.
Los materiales cubren una gama de capacidades estadísticas, incluyendo inferencia causal para evaluar efectos de tratamiento y ponderación de post-estratificación para ajustar datos de muestra para la representación de la población. Otras áreas cubiertas incluyen análisis de supervivencia para modelar duraciones de eventos y la aplicación de paquetes estadísticos curados.
Features
- Bayesian Estimation Guides - Provides structured educational resources and code implementations for mastering Bayesian data analysis and causal modeling.
- Bayesian Statistics Courseware - Provides a comprehensive collection of instructional materials, problem sets, and solutions for learning Bayesian statistics.
- Causal Inference Tools - Provides tools and educational content for identifying cause-effect relationships in observational data.
- Causal Effect Estimators - Implements methods for estimating the magnitude of causal effects and generalizing those effects across populations.
- Exercise-Solution Pairings - Provides educational structures that link specific problem statements directly to verified algorithmic implementations.
- Curriculum Sequencing - Arranges learning materials in a structured sequence to guide the progression from basic to complex causal modeling.
- Course Assignments - Offers a set of structured assignments and solutions for practicing Bayesian data analysis techniques.
- Problem Set Collections - Provides structured problem sets and corresponding solutions to support the study of Bayesian data analysis.
- Bayesian Statistical Modeling - Implements probabilistic models with priors and likelihoods across multiple languages to explore computational approaches.
- Cross-Language Implementations - Provides Bayesian model implementations across multiple programming languages to demonstrate various computational approaches.
- Study Guides - Offers educational resources and study guides focused on evaluating treatment effects and generalizing outcomes.
- Causal Effect Estimators - Provides methods for estimating the magnitude of causal relationships and evaluating treatment effects from observational data.
- Survival Analysis - Provides instructional materials and code for modeling the time until a specific event occurs.
- Instructional Animation Scripts - Ships scripts that render instructional animations and plots to visualize complex statistical analysis concepts.
- Statistical Data Visualizations - Uses visual representations and plots to analyze and communicate relationships and patterns within statistical data.
- Cross-Language Implementation Maps - Provides collections of identical logic across different languages to illustrate syntax and runtime differences for educational purposes.
