University of California, Santa Cruz

Bayesian Statistics: Capstone Project

University of California, Santa Cruz

Bayesian Statistics: Capstone Project

This course is part of Bayesian Statistics Specialization

Jizhou Kang

Instructor: Jizhou Kang

Access provided by Kalinga Institute of Industrial Technology

1,557 already enrolled

Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace
Gain insight into a topic and learn the fundamentals.
Advanced level

Recommended experience

1 week to complete
at 10 hours a week
Flexible schedule
Learn at your own pace

What you'll learn

  • Demonstrate a wide range of skills and knowledge in Bayesian statistics.

  • Explain essential concepts in Bayesian statistics.

  • Apply what you know to real-world data.

Details to know

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Assessments

6 assignments¹

AI Graded see disclaimer
Taught in English

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This course is part of the Bayesian Statistics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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  • Gain a foundational understanding of a subject or tool
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There are 4 modules in this course

In this module, we will introduce conjugate Bayesian analysis for the autoregressive (AR) models.

What's included

3 videos7 readings2 assignments

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.

What's included

2 videos2 readings2 assignments

In this module, we will perform Bayesian analysis for location mixture of AR(p) models.

What's included

4 videos3 readings2 assignments

In this module, we will use everything we have learned up until now to perform a mixture model on time series data.

What's included

1 reading1 peer review

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Instructor

Jizhou Kang
University of California, Santa Cruz
1 Course 1,557 learners

Offered by

University of California, Santa Cruz

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¹ Some assignments in this course are AI-graded. For these assignments, your data will be used in accordance with Coursera's Privacy Notice.