**Contact Info**

Department of Applied Mathematics

University of Waterloo

Waterloo, Ontario

Canada N2L 3G1

Phone: 519-888-4567, ext. 32700

Fax: 519-746-4319

PDF files require Adobe Acrobat Reader

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Thursday, May 21, 2020 — 3:00 PM EDT

MS Teams

Supranta Sarma Boruah’s | Applied Math, University of Waterloo

Bayesian data analysis with Markov Chain Monte Carlo (MCMC) methods

Bayesian data analysis techniques have found a widespread applications in the scientific fields over the last few decades. In particular. Markov Chain Monte Carlo methods are widely used for statistical inference.

In this seminar series, I will introduce the concepts of Bayesian data analysis, in particular, using MCMC methods. I will start with the familiar example of linear regression, interpreted in the Bayesian language and then graduate to examples with real cosmological data. In the second part of the series, I will introduce MCMC algorithms beyond the usual Metropolis-Hastings algorithm, which are beginning to be used more extensively and diagnostic tests useful for analyzing properties of the MCMC runs. Finally, in the third part of the series, I will introduce the concept of Bayesian hierarchical modelling, which through its probabilistic modelling captures known relations between different variables.

The sessions will be a hands-on. Bringing laptops with jupyter notebook installed is encouraged.

**Contact Info**

Department of Applied Mathematics

University of Waterloo

Waterloo, Ontario

Canada N2L 3G1

Phone: 519-888-4567, ext. 32700

Fax: 519-746-4319

PDF files require Adobe Acrobat Reader

University of Waterloo

University of Waterloo

43.471468

-80.544205

200 University Avenue West

Waterloo,
ON,
Canada
N2L 3G1

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