rmcelreath/stat_rethinking_2022
Stat Rethinking 2022
Dieses Projekt ist eine Sammlung von Kursmaterialien und Bildungsressourcen zur Bayes-Statistik. Es bietet Lehrmaterialien, Aufgabenblätter und Lösungen, die für das Erlernen von Bayes-Datenanalyse und kausaler Modellierung konzipiert sind.
Das Repository enthält eine Suite statistischer Datenvisualisierungsskripte, die zur Erstellung von Lehranimationen und Diagrammen verwendet werden. Es enthält zudem Codebeispiele, die Bayes-Modellierung und Überlebenszeitanalyse über mehrere Programmiersprachen hinweg implementieren, um verschiedene rechnerische Ansätze zu demonstrieren.
Die Materialien decken ein Spektrum statistischer Funktionen ab, einschließlich kausaler Inferenz zur Evaluierung von Behandlungseffekten und Post-Stratification-Gewichtung zur Anpassung von Stichprobendaten an die Bevölkerungsrepräsentation. Weitere abgedeckte Bereiche umfassen Überlebenszeitanalyse zur Modellierung von Ereignisdauern und die Anwendung kuratierter statistischer Pakete.
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.
