This is the capstone project for UC Santa Cruz's Bayesian Statistics Specialization. It is an opportunity for you to demonstrate a wide range of skills and knowledge in Bayesian statistics and to apply what you know to real-world data. You will review essential concepts in Bayesian statistics with lecture videos and quizzes, and you will perform a complex data analysis and compose a report on your methods and results.
oferecido por
Programa de cursos integrados EstatÃstica BayesianaUniversidade da Califórnia, Santa CruzInformações sobre o curso
Prazos flexÃveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 5 de 5 no
NÃvel avançado
Familiarity with calculus-based probability, maximum-likelihood estimation, Bayesian inference, mixture models, and time-series analysis.
Aprox. 12 horas para completar
Inglês
Legendas: Inglês
Prazos flexÃveis
Redefinir os prazos de acordo com sua programação.
Certificados compartilháveis
Tenha o certificado após a conclusão
100% on-line
Comece imediatamente e aprenda em seu próprio cronograma.
Curso 5 de 5 no
NÃvel avançado
Familiarity with calculus-based probability, maximum-likelihood estimation, Bayesian inference, mixture models, and time-series analysis.
Aprox. 12 horas para completar
Inglês
Legendas: Inglês
oferecido por
Universidade da Califórnia, 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.
Programa - O que você aprenderá com este curso
3 horas para concluir
Bayesian Conjugate Analysis for Autogressive Time Series Models
In this module, we will introduce conjugate Bayesian analysis for the autoregressive (AR) models.
3 horas para concluir
3 vÃdeos (Total 26 mÃn.), 7 leituras, 2 testes
2 horas para concluir
Model Selection Criteria
In this module, we will introduce some criteria that can be used in selecting the order of AR processes and the number of mixing components, which will be used later when we introduce mixture of AR models.
2 horas para concluir
2 vÃdeos (Total 20 mÃn.), 2 leituras, 2 testes
2 horas para concluir
Bayesian location mixture of AR(P) model
In this module, we will perform Bayesian analysis for location mixture of AR(p) models.
2 horas para concluir
4 vÃdeos (Total 45 mÃn.), 3 leituras, 2 testes
5 horas para concluir
Peer-reviewed data analysis project
In this module, we will use everything we have learned up until now to perform a mixture model on time series data.
5 horas para concluir
1 leitura
Sobre Programa de cursos integrados EstatÃstica Bayesiana
This Specialization is intended for all learners seeking to develop proficiency in statistics, Bayesian statistics, Bayesian inference, R programming, and much more. Through four complete courses (From Concept to Data Analysis; Techniques and Models; Mixture Models; Time Series Analysis) and a culminating project, you will cover Bayesian methods — such as conjugate models, MCMC, mixture models, and dynamic linear modeling — which will provide you with the skills necessary to perform analysis, engage in forecasting, and create statistical models using real-world data.
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