Bayesian Computational Statistics
By Coursera
on Coursera
· Data Science
About This Course
A rigorous introduction to the theory of Bayesian Statistical Inference and Data Analysis, including prior and posterior distributions, Bayesian estimation and testing, Bayesian computation theories and methods, and implementation of Bayesian computation methods using popular statistical software. Required Textbook: Gelman, A., Carlin, J. B., Stern, H. S., Rubin, D. B. (2013) Bayesian Data Analysis, Third Edition, Chapman & Hall/CRC. Software Requirements: R or Python, Word processing (such as Word, Pages, LaTeX, etc)
Instructor
Shahrzad (Sara) Jamshidi
Frequently Asked Questions
How much does Bayesian Computational Statistics cost?
Visit the Bayesian Computational Statistics course page for current pricing and available discounts.
Who teaches Bayesian Computational Statistics?
Bayesian Computational Statistics is taught by Shahrzad (Sara) Jamshidi, Illinois Tech.
What skill level is Bayesian Computational Statistics for?
This course is designed for beginner learners.