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.
提供方
贝叶斯统计 专项课程加州大学圣克鲁兹分校课程信息
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 5 门课程（共 5 门）
高级
Familiarity with calculus-based probability, maximum-likelihood estimation, Bayesian inference, mixture models, and time-series analysis.
完成时间大约为12 小时
英语（English）
字幕：英语（English）
可灵活调整截止日期
根据您的日程表重置截止日期。
可分享的证书
完成后获得证书
100% 在线
立即开始，按照自己的计划学习。
第 5 门课程（共 5 门）
高级
Familiarity with calculus-based probability, maximum-likelihood estimation, Bayesian inference, mixture models, and time-series analysis.
完成时间大约为12 小时
英语（English）
字幕：英语（English）
提供方
加州大学圣克鲁兹分校
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.
授课大纲 - 您将从这门课程中学到什么
完成时间为 3 小时
Bayesian Conjugate Analysis for Autogressive Time Series Models
In this module, we will introduce conjugate Bayesian analysis for the autoregressive (AR) models.
完成时间为 3 小时
3 个视频 （总计 26 分钟）, 7 个阅读材料, 2 个测验
完成时间为 2 小时
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.
完成时间为 2 小时
2 个视频 （总计 20 分钟）, 2 个阅读材料, 2 个测验
完成时间为 2 小时
Bayesian location mixture of AR(P) model
In this module, we will perform Bayesian analysis for location mixture of AR(p) models.
完成时间为 2 小时
4 个视频 （总计 45 分钟）, 3 个阅读材料, 2 个测验
完成时间为 5 小时
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.
完成时间为 5 小时
1 个阅读材料
关于 贝叶斯统计 专项课程
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.
常见问题
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