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Bayesian Computational Statistics · LearnSpace
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Bayesian Computational Statistics

Курс от Illinois Tech
Средний≈ 88.7 чАнглийский
О курсеНавыкиПрограммаПреподаватели

О курсе

A rigorous introduction to the theory of Bayesian Statistical Inference and Data Analysis, including prior and posterior distributions, Bayesian estimation and testing, Bayesian computation theories and methods, and implementation of Bayesian computation methods using popular statistical software. Required Textbook: Gelman, A., Carlin, J. B., Stern, H. S., Rubin, D. B. (2013) Bayesian Data Analysis, Third Edition, Chapman & Hall/CRC. Software Requirements: R or Python, Word processing (such as Word, Pages, LaTeX, etc)

Навыки, которые вы освоите

Bayesian StatisticsStatistical ModelingSimulationsRegression AnalysisModel EvaluationStatistical InferenceNumerical AnalysisLogistic RegressionR ProgrammingMarkov ModelStatistical ProgrammingData Analysis SoftwareStatistical SoftwareStatistical AnalysisProbability DistributionSampling (Statistics)Data AnalysisStatistical MethodsR (Software)Probability

Программа курса

9 модулей · 180 учебных материалов

01Module 1: Fundamentals of Bayesian Inference22 материалов

Course Welcome

Course OverviewВидеоInstructor IntroductionВидеоSyllabusЧтениеMeet and Greet DiscussionОбсуждение

Module 1 Introduction

Учитесь у экспертов

Shahrzad (Sara) Jamshidi

Преподаватель курса

Bayesian Computational Statistics
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Обучение на Coursera

≈ 88.7 ч

9 модулей

Язык: Английский

Субтитры: Арабский, Французский, Итальянский, Бразильский португальский, Корейский, Немецкий, Испанский, Японский, Венгерский

Часть программы вашего университета
Module 1 IntroductionВидео

Lesson 1: Bayesian Probability

Bayesian Probability ReadingsЧтениеBayes' rule and its consequences Pt. 1ВидеоBayes' rule and its consequences Pt. 2ВидеоBayesian Probability QuizЗадание

Lesson 2: Bayesian Inference

Bayesian ReadingЧтениеFundamentals of Bayesian inference Pt. 1ВидеоFundamentals of Bayesian inference Pt. 2ВидеоFundamentals of Bayesian inference Pt. 3ВидеоFundamentals of Bayesian inference Pt. 4ВидеоBayesian Inference QuizЗадание

Lesson 3: Computation

Computation ReadingЧтениеBayesian Computation Pt. 1ВидеоBayesian Computation Pt. 2ВидеоComputation QuizЗаданиеModule 1 - Lesson 3 - RStudio LabЛабораторная

Module 1 Summative Assessment

Module 1 Summative AssessmentЗадание

Module 1 Summary

Module 1 SummaryЧтение
02Module 2: Single Parameter Models26 материалов

Module 2 Introduction

Module 2 IntroductionВидео

Lesson 1: Estimating Probabilities and Posterior Distributions

Estimating Probabilities and Posterior Distributions ReadingsЧтениеBinomial and Posterior Distributions Pt. 1ВидеоBinomial and Posterior Distributions Pt. 2ВидеоBinomial and Posterior Distributions Pt. 3ВидеоBinomial and Posterior Distributions Pt. 4ВидеоBinomial and Posterior Distributions Pt. 5ВидеоBinomial and Posterior Distributions Pt. 6ВидеоEstimating Probabilities and Posterior QuizЗадание

Lesson 2: Summarizing Posterior Inference and Prior Distributions

Summarizing Posterior Inference and Prior Distributions ReadingsЧтениеPriors Pt. 1ВидеоPriors Pt. 2ВидеоPriors Pt. 3ВидеоSummarizing Posterior Inference and Prior Distributions QuizЗадание

Lesson 3: Normal Distribution and Other Single-Parameter Models

Normal Distribution and Other Single-Parameter Models ReadingЧтениеOther Single-Parameter Models Pt. 1ВидеоOther Single-Parameter Models Pt. 2ВидеоOther Single-Parameter Models Pt. 3ВидеоOther Single-Parameter Models Pt. 4ВидеоOther Single-Parameter Models Pt. 5Видео

Module 2 Summative Assessment

Module 2 Summative AssessmentЗадание

Module 2 Summary

Module 2 SummaryЧтение
03Module 3: Multiparameter Models25 материалов

Module 3 Introduction

Module 3 IntroductionВидео

Lesson 1: Handling Normal Data and Nuisance Parameters

Multiparameter Models ReadingЧтениеNuisance Parameters Pt. 1ВидеоNuisance Parameters Pt. 2ВидеоNuisance Parameters Pt. 3ВидеоNuisance Parameters Pt. 4ВидеоNuisance Parameters Pt. 5ВидеоNuisance Parameters Pt. 6ВидеоNuisance Parameters Pt. 7ВидеоHandling Normal Data and Nuisance Parameters QuizЗаданиеModule 3 - Lesson 1 - RStudio LabЛабораторная

Lesson 2: Conjugate Priors and Multivariate Normal Models

Conjugate Priors and Multivariate Normal Models ReadingsЧтениеConjugate Priors Pt. 1ВидеоConjugate Priors Pt. 2ВидеоConjugate Priors Pt. 3ВидеоConjugate Priors and Multivariate Normal Models QuizЗаданиеModule 3 - Lesson 2 - RStudio LabЛабораторная

Lesson 3: Advanced Multivariate Models and Practical Applications

Advanced Multivariate Models and Practical Applications ReadingЧтениеMore Models and Applications Pt. 1ВидеоMore Models and Applications Pt. 2ВидеоAdvanced Multivariate Models and Practical Applications QuizЗаданиеModule 3 - Lesson 3 - RStudio LabЛабораторная

Module 3 Summative Assessment

Module 3 Summative AssessmentЗадание

Module 3 Summary

Module 3 SummaryЧтениеInsights from an Industry Leader: Learn More About Our ProgramЧтение
04Module 4: Large-Sample Inference and Frequency Properties23 материалов

Module 4 Introduction

Module 4 IntroductionВидео

Lesson 1: Normal Approximation and Its Applications

Normal Approximation and Its Applications ReadingЧтениеNormal Approximation Pt. 1ВидеоNormal Approximation Pt. 2ВидеоNormal Approximation Pt. 3ВидеоNormal Approximation Pt. 4ВидеоNormal Approximation Pt. 5ВидеоNormal Approximation and Its Applications QuizЗаданиеModule 4 - Lesson 1 - RStudio LabЛабораторная

Lesson 2: Exploring Large-Sample Theory and Counterexamples

Exploring Large-Sample Theory and Counterexamples ReadingsЧтениеLarge-Sample Theory Pt. 1ВидеоLarge-Sample Theory Pt. 2ВидеоLarge-Sample Theory Pt. 3ВидеоLarge-Sample Theory Pt. 4ВидеоLarge-Sample Theory Pt. 5Видео

Lesson 3: Frequency Properties and Broader Interpretations of Bayesian Methods

Frequency Properties and Broader Interpretations of Bayesian ReadingsЧтениеFrequency Properties Pt. 1ВидеоFrequency Properties Pt. 2ВидеоFrequency Properties and Broader Interpretations of Bayesian Methods QuizЗадание

Module 4 Summative Assessment

Module 4 Summative AssessmentЗадание

Module 4 Summary

Module 4 SummaryЧтение
05Module 5: Hierarchical Models18 материалов

Module 5 Introduction

Module 5 IntroductionВидео

Lesson 1: Parameterized Priors and the Concept of Exchangeability

Parameterized Priors and the Concept of Exchangeability ReadingsЧтениеParameterized Priors and Exchangeability Pt. 1ВидеоParameterized Priors and Exchangeability Pt. 2ВидеоParameterized Priors and the Concept of Exchangeability QuizЗадание

Lesson 2: Analysis and Applications of Hierarchical Models

Analysis and Applications of Hierarchical Models ReadingsЧтениеHierarchical Models Pt. 1ВидеоHierarchical Models Pt. 2ВидеоHierarchical Models Pt. 3ВидеоHierarchical Models Pt. 4ВидеоAnalysis and Applications of Hierarchical Models QuizЗадание

Lesson 3: Computational Techniques and Model Validation

Computational Techniques and Model Validation ReadingЧтениеModel Validation Pt. 1ВидеоModel Validation Pt. 2ВидеоComputational Techniques and Model Validation QuizЗаданиеModule 5 - Lesson 3 - RStudio LabЛабораторная

Module 5 Summative Assessment

Module 5 Summative AssessmentЗадание

Module 5 Summary

Module 5 SummaryЧтение
06Module 6: Bayesian Computation21 материалов

Module 6 Introduction

Module 6 IntroductionВидео

Lesson 1: Numerical Methods and Approximations in Bayesian Computation

Numerical Methods and Approximations in Bayesian Computation ReadingsЧтениеNumerical Methods and Approximation Pt. 1ВидеоNumerical Methods and Approximation Pt. 2ВидеоNumerical Methods and Approximation Pt. 3ВидеоNumerical Methods and Approximations in Bayesian Computation QuizЗадание

Lesson 2: Simulation Techniques for Bayesian Inference

Simulation Techniques for Bayesian Inference ReadingsЧтениеSimulation Techniques for Bayesian Inference Pt. 1ВидеоSimulation Techniques for Bayesian Inference Pt. 2ВидеоSimulation Techniques for Bayesian Inference Pt. 3ВидеоSimulation Techniques for Bayesian Inference Pt. 4ВидеоSimulation Techniques for Bayesian Inference QuizЗадание

Lesson 3: Advanced Markov Chain Methods for Bayesian Computation

Advanced Markov Chain Methods for Bayesian Computation ReadingsЧтениеMarkov Chain Methods Pt. 1ВидеоMarkov Chain Methods Pt. 2ВидеоMarkov Chain Methods Pt. 3ВидеоMarkov Chain Methods Pt. 4ВидеоAdvanced Markov Chain Methods for Bayesian Computation QuizЗадание

Module 6 Summative Assessment

Module 6 Summative AssessmentЗадание

Module 6 Summary

Module 6 SummaryЧтение
07Module 7: Regression Models28 материалов

Module 7 Introduction

Module 7 IntroductionВидео

Lesson 1: Foundations of Bayesian Regression Analysis

Foundations of Bayesian Regression Analysis ReadingsЧтениеFoundations of Bayesian Regression Analysis Pt. 1ВидеоFoundations of Bayesian Regression Analysis Pt. 2ВидеоFoundations of Bayesian Regression Analysis Pt. 3ВидеоFoundations of Bayesian Regression Analysis Pt. 4ВидеоFoundations of Bayesian Regression Analysis Pt. 5ВидеоFoundations of Bayesian Regression Analysis Pt. 6ВидеоFoundations of Bayesian Regression Analysis Pt. 7ВидеоFoundations of Bayesian Regression Analysis QuizЗадание

Lesson 2: Advanced Techniques in Hierarchical Linear Models

Advanced Techniques in Hierarchical Linear Models ReadingsЧтениеHierarchical Linear Models Pt. 1ВидеоHierarchical Linear Models Pt. 2ВидеоHierarchical Linear Models Pt. 3ВидеоHierarchical Linear Models Pt. 4ВидеоAdvanced Techniques in Hierarchical Linear Models QuizЗадание

Lesson 3: Exploring Generalized Linear Models in Bayesian Context

Exploring Generalized Linear Models in Bayesian Context ReadingsЧтениеGeneralized Linear Models Pt. 1ВидеоGeneralized Linear Models Pt. 2ВидеоGeneralized Linear Models Pt. 3ВидеоGeneralized Linear Models Pt. 4ВидеоGeneralized Linear Models Pt. 5Видео

Module 7 Summative Assessment

Module 7 Summative AssessmentЗадание

Module 7 Summary

Module 7 SummaryЧтение
08Module 8: Advanced Topics16 материалов

Module 8 Introduction

Module 8 IntroductionВидео

Lesson 1: Setting Up and Interpreting Mixture Models

Setting Up and Interpreting Mixture Models ReadingsЧтениеSetting Up and Interpreting Mixture Models Pt. 1ВидеоSetting Up and Interpreting Mixture Models Pt. 2ВидеоSetting Up and Interpreting Mixture Models Pt. 3ВидеоSetting Up and Interpreting Mixture Models Pt. 4ВидеоSetting Up and Interpreting Mixture Models Pt. 5ВидеоSetting Up and Interpreting Mixture Models QuizЗадание

Lesson 2: Practical Applications and Computational Challenges

Practical Applications and Computational Challenges ReadingsЧтениеApplications of Mixture Models Pt. 1ВидеоApplications of Mixture Models Pt. 2ВидеоApplications of Mixture Models Pt. 3ВидеоPractical Applications and Computational Challenges QuizЗаданиеModule 8 - Lesson 2 - RStudio LabЛабораторная

Module 8 Summative Assessment

Module 8 Summative Assessment Задание

Module 8 Summary

Module 8 SummaryЧтение
09Summative Course Assessment1 материалов

Summative Course Assessment

Summative Course AssessmentЗадание
Other Single-Parameter Models Pt. 6Видео
Other Single-Parameter Models Pt. 7Видео
Normal Distribution and Other Single-Parameter Models QuizЗадание
Module 2 - Lesson 3 - RStudio LabЛабораторная
Large-Sample Theory Pt. 6Видео
Exploring Large-Sample Theory and Counterexamples QuizЗадание
Module 6 - Lesson 3 - RStudio LabЛабораторная
Generalized Linear Models Pt. 6Видео
Generalized Linear Models Pt. 7Видео
Exploring Generalized Linear Models in Bayesian Context QuizЗадание
Module 7 - Lesson 3 - RStudio LabЛабораторная