This course is part of the Bayesian Statistics Specialization

Jizhou Kang

Offered By

Bayesian Statistics SpecializationUniversity of California, Santa Cruz

About this Course

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.

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Shareable Certificate

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Course 5 of 5 in the

Bayesian Statistics Specialization

Advanced Level

Familiarity with calculus-based probability, maximum-likelihood estimation, Bayesian inference, mixture models, and time-series analysis.

Approx. 11 hours to complete

English

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Flexible deadlines

Reset deadlines in accordance to your schedule.

Shareable Certificate

Earn a Certificate upon completion

100% online

Start instantly and learn at your own schedule.

Course 5 of 5 in the

Bayesian Statistics Specialization

Advanced Level

Familiarity with calculus-based probability, maximum-likelihood estimation, Bayesian inference, mixture models, and time-series analysis.

Approx. 11 hours to complete

English

Could your company benefit from training employees on in-demand skills?

Try Coursera for Business

Instructor

Jizhou Kang

Statistics

117 Learners

1 Course

Offered by

University of California, Santa Cruz

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Syllabus - What you will learn from this course

Week1

Week 1

3 hours to complete

Bayesian Conjugate Analysis for Autogressive Time Series Models

3 hours to complete

3 videos (Total 26 min), 7 readings, 2 quizzes

Week2

Week 2

2 hours to complete

Model Selection Criteria

2 hours to complete

2 videos (Total 20 min), 2 readings, 2 quizzes

Week3

Week 3

2 hours to complete

Bayesian location mixture of AR(P) model

2 hours to complete

4 videos (Total 45 min), 3 readings, 2 quizzes

4 videos

Prediction for Location Mixture of AR Models4mFull conditional distributions of model parameters25mCoding the Gibbs sampler9m Prediction for location mixture of AR model4m

3 readings

Sample code for the Gibbs sampler10mDetermine the number of components10mLocation and scale mixture of AR model10m

2 practice exercises

Fit a location mixture of AR model30mDetermine number of components for the mixture model30m

Week4

Week 4

5 hours to complete

Peer-reviewed data analysis project

5 hours to complete

1 reading

About the Bayesian Statistics Specialization

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.

Frequently Asked Questions

When will I have access to the lectures and assignments?
Access to lectures and assignments depends on your type of enrollment. If you take a course in audit mode, you will be able to see most course materials for free. To access graded assignments and to earn a Certificate, you will need to purchase the Certificate experience, during or after your audit. If you don't see the audit option:
The course may not offer an audit option. You can try a Free Trial instead, or apply for Financial Aid.
The course may offer 'Full Course, No Certificate' instead. This option lets you see all course materials, submit required assessments, and get a final grade. This also means that you will not be able to purchase a Certificate experience.
What will I get if I subscribe to this Specialization?
When you enroll in the course, you get access to all of the courses in the Specialization, and you earn a certificate when you complete the work. 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.
Is financial aid available?
Yes. In select learning programs, you can apply for financial aid or a scholarship if you can’t afford the enrollment fee. If fin aid or scholarship is available for your learning program selection, you’ll find a link to apply on the description page.

More questions? Visit the Learner Help Center.

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Bayesian Statistics: Capstone Project

About this Course