Informações sobre o curso
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This is the second of a two-course sequence introducing the fundamentals of Bayesian statistics. It builds on the course Bayesian Statistics: From Concept to Data Analysis, which introduces Bayesian methods through use of simple conjugate models. Real-world data often require more sophisticated models to reach realistic conclusions. This course aims to expand our “Bayesian toolbox” with more general models, and computational techniques to fit them. In particular, we will introduce Markov chain Monte Carlo (MCMC) methods, which allow sampling from posterior distributions that have no analytical solution. We will use the open-source, freely available software R (some experience is assumed, e.g., completing the previous course in R) and JAGS (no experience required). We will learn how to construct, fit, assess, and compare Bayesian statistical models to answer scientific questions involving continuous, binary, and count data. This course combines lecture videos, computer demonstrations, readings, exercises, and discussion boards to create an active learning experience. The lectures provide some of the basic mathematical development, explanations of the statistical modeling process, and a few basic modeling techniques commonly used by statisticians. Computer demonstrations provide concrete, practical walkthroughs. Completion of this course will give you access to a wide range of Bayesian analytical tools, customizable to your data....
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cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Intermediate Level

Nível intermediário

Clock

Approx. 34 hours to complete

Sugerido: 5 weeks of study, 4-6 hours/week....
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English

Legendas: English...

Habilidades que você terá

Gibbs SamplingBayesian StatisticsBayesian InferenceR Programming
Globe

cursos 100% online

Comece imediatamente e aprenda em seu próprio cronograma.
Calendar

Prazos flexíveis

Redefinir os prazos de acordo com sua programação.
Intermediate Level

Nível intermediário

Clock

Approx. 34 hours to complete

Sugerido: 5 weeks of study, 4-6 hours/week....
Comment Dots

English

Legendas: English...

Programa - O que você aprenderá com este curso

Week
1
Clock
4 horas para concluir

Statistical modeling and Monte Carlo estimation

Statistical modeling, Bayesian modeling, Monte Carlo estimation...
Reading
11 vídeos (Total de 99 min), 4 leituras, 4 testes
Video11 videos
Objectives7min
Modeling process8min
Components of Bayesian models8min
Model specification7min
Posterior derivation9min
Non-conjugate models7min
Monte Carlo integration9min
Monte Carlo error and marginalization6min
Computing examples15min
Computing Monte Carlo error13min
Reading4 leituras
Module 1 assignments and materials3min
Reference: Common probability distributionsmin
Code for Lesson 3min
Markov chains20min
Quiz4 exercícios práticos
Lesson 120min
Lesson 225min
Lesson 330min
Markov chains20min
Week
2
Clock
5 horas para concluir

Markov chain Monte Carlo (MCMC)

Metropolis-Hastings, Gibbs sampling, assessing convergence...
Reading
11 vídeos (Total de 129 min), 7 leituras, 4 testes
Video11 videos
Demonstration10min
Random walk example, Part 112min
Random walk example, Part 216min
Download, install, setup3min
Model writing, running, and post-processing12min
Multiple parameter sampling and full conditional distributions8min
Conditionally conjugate prior example with Normal likelihood10min
Computing example with Normal likelihood16min
Trace plots, autocorrelation17min
Multiple chains, burn-in, Gelman-Rubin diagnostic8min
Reading7 leituras
Module 2 assignments and materials3min
Code for Lesson 4min
Alternative MCMC software10min
Code from JAGS introductionmin
Code for Lesson 510min
Autocorrelation10min
Code for Lesson 6min
Quiz4 exercícios práticos
Lesson 420min
Lesson 530min
Lesson 620min
MCMC45min
Week
3
Clock
6 horas para concluir

Common statistical models

Linear regression, ANOVA, logistic regression, multiple factor ANOVA...
Reading
11 vídeos (Total de 131 min), 5 leituras, 5 testes
Video11 videos
Setup in R9min
JAGS model (linear regression)12min
Model checking17min
Alternative models10min
Deviance information criterion (DIC)4min
Introduction to ANOVA10min
One way model using JAGS18min
Introduction to logistic regression6min
JAGS model (logistic regression)18min
Prediction15min
Reading5 leituras
Module 3 assignments and materials3min
Code for Lesson 7min
Code for Lesson 8min
Code for Lesson 9min
Multiple factor ANOVA20min
Quiz5 exercícios práticos
Lesson 7 Part A30min
Lesson 7 Part B30min
Lesson 830min
Lesson 945min
Common models and multiple factor ANOVA30min
Week
4
Clock
5 horas para concluir

Count data and hierarchical modeling

Poisson regression, hierarchical modeling...
Reading
10 vídeos (Total de 106 min), 7 leituras, 4 testes
Video10 videos
JAGS model (Poisson regression)17min
Predictive distributions11min
Correlated data8min
Prior predictive simulation10min
JAGS model and model checking (hierarchical modeling)13min
Posterior predictive simulation8min
Linear regression example7min
Linear regression example in JAGS10min
Mixture model in JAGS13min
Reading7 leituras
Module 4 assignments and materials3min
Prior sensitivity analysis20min
Code for Lesson 10min
Normal hierarchical model20min
Applications of hierarchical modeling10min
Code and data for Lesson 11min
Mixture model introduction, data, and code20min
Quiz4 exercícios práticos
Lesson 1040min
Lesson 11 Part A40min
Lesson 11 Part B30min
Predictive distributions and mixture models30min

Instrutores

Matthew Heiner

Doctoral Student
Applied Mathematics and Statistics

Sobre University of California, Santa Cruz

UC Santa Cruz is an outstanding public research university with a deep commitment to undergraduate education. It’s a place that connects people and programs in unexpected ways while providing unparalleled opportunities for students to learn through hands-on experience....

Perguntas Frequentes – FAQ

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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