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Bayesian Statistical Concepts and Methods · LearnSpace
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Bayesian Statistical Concepts and Methods

Курс от Arizona State University
Средний≈ 5.5 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

Welcome to Bayesian Statistical Concepts and Methods. In this course, you will use Bayesian methods in data analysis and modeling; work with posterior distributions, distributions without closed form, directed acyclic graphs, Markov Chain Monte Carlo algorithms; and employ R and the Stan platform for statistical modeling. You will also be introduced to Bayesian hierarchical models, which are useful for the interpretation of multi-level data (sub-group versus group).

Навыки, которые вы освоите

Network ModelData-Driven Decision-MakingR ProgrammingSampling (Statistics)Statistical AnalysisR (Software)Statistical ModelingBayesian StatisticsStatistical MethodsMarkov ModelProbability DistributionSimulationsStatistical InferenceDependency AnalysisStatistical ProgrammingData AnalysisBayesian Network

Программа курса

3 модулей · 36 учебных материалов

01Course Introduction9 материалов

Introduction and Resources

Course IntroductionВидеоCourse Resources and Peer ReviewsЧтение

Meet the Instructors

Instructor BiosЧтение

Concepts & Fundamentals of Bayesian Analysis

Concepts and Fundamentals of Bayesian Analysis Lecture - Video Segment OverviewЧтение

Учитесь у экспертов

George Runger

Professor of Engineering

Edgar Hassler

Principal Data Scientist

Bayesian Statistical Concepts and Methods
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Обучение откроется на Coursera
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Обучение на Coursera

≈ 5.5 ч

3 модулей

Язык: Английский

Часть программы вашего университета
Segment 1: Introduction to Bayesian AnalysisВидео
Segment 2: Bayesian Estimation of Parameters: Concepts and Mathematical ExpressionВидео
Segment 3: Example: Bayes Estimator for the Mean of a Normal DistributionВидео
Segment 4: Conclusions: Bayesian Lessons from the ExampleВидео
Practice Quiz for Overview of Bayesian Data AnalysisЗадание
02Methods for Bayesian Simulation and Estimation12 материалов

Bayesian Models, Posterior Distributions, and Distributions Without Closed Form

Bayesian Models and Posterior Distributions Lecture - Video Segment OverviewЧтениеSegment 1: Working with Bayesian Models: ConventionsВидеоSegment 2: Example, Part A: Silicon Wafer Cleaning - Priors and PosteriorsВидеоSegment 3: Example, Part B: Silicon Wafer Cleaning - Wafer Thickness Prediction (Fixed Mean) and DecisionВидеоSegment 4: Example, Part C: Silicon Wafer Cleaning - Wafer Thickness Prediction and Decision (Uncertain Mean and Variance) Using Stan ModelВидеоSegment 5: Working with Bayesian Models: SummaryВидео

Modeling Probabalistic Relationships with Bayesian Networks

Bayesian Networks Lecture - Video Segment OverviewЧтениеSegment 1: Introduction to Bayesian Networks and Covid Testing ExampleВидеоSegment 2: Cancer Diagnosis: Building and Querying a Bayesian Network Using RВидеоSegment 3: Advanced Queries and Evidence Updates in Bayesian NetworksВидеоSegment 4: Applications and Information Value, Parameter Fitting, and ExtensionsВидеоPractice Quiz for Bayesian Simulation and EstimationЗадание
03Applied Bayesian Modeling with Stan15 материалов

Modeling Using Stan

Modeling Using Stan Lecture - Video Segment OverviewЧтениеSegment 1: Using Stan Function in R to Assemble Bayesian or Other ModelsВидеоSegment 2: Stan Model Definition and SyntaxВидеоSegment 3: Stan Sampling and Posterior AnalysisВидеоSegment 4: Advanced Stan Modeling: Bayesian FitВидеоSegment 5: Optimization and Simulation Studies in StanВидео

Stan Diagnostics

Stan Diagnostics Lecture - Video Segment OverviewЧтениеSegment 1: Diagnosing Stan Output: Common Diagnostic Issues and MetricsВидеоSegment 2: The "Eight Schools" Case Example: Applied Diagnostics and Plots Reveal ProblemsВидеоSegment 3: Understanding Stan Divergences and Errors: Advanced Diagnostic Tools and StrategiesВидеоSegment 4: Reparameterization and Model ImprovementВидеоPractice Quiz for Modeling Using StanЗадание

Using Bayesian Hierarchical Models to Improve Interpretation of Multi-Level Data

Partial PoolingВидеоStan ResourcesЧтениеMini-Project for Modern Statistics for Data-Driven Decision-MakingВзаимная проверка