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    Education: Course live online: Intro Bayesian Analyses
    Submitted by Soledad De Esteban Trivigno; posted on Thursday, March 23, 2023

    May 8-12, 2023
    https://www.transmittingscience.com/courses/statistics-and-bioinformatics/introduction-bayesian-inference-practice/

    Registration is open for the course Introduction to Bayesian Inference in Practice – 6th edition. This course will be held live online (synchronous). Max 18 participants.

    Dates: May 8th-12th, 2023. Online live sessions from Monday to Friday; 13:00 to 17:00 (Madrid time zone).

    Instructors: Dr. Daniele Silvestro (University of Gothenburg, Sweden) and Tobias Andermann (University of Gothenburg, Sweden)

    COURSE OVERVIEW

    This course is based on the assumption that the easiest way to understand the principles of Bayesian inference and the functioning of the main algorithms is to implement these methods yourself.

    The instructor will outline the relevant concepts and basic theory, but the focus of the course will be to learn how to do Bayesian inference in practice. He will show how to implement the most common algorithms to estimate parameters based on posterior probabilities, such as Markov Chain Monte Carlo samplers, and how to build hierarchical models.

    He will also touch upon hypothesis testing using Bayes factors and Bayesian variable selection.

    The course will take a learn-by-doing approach, in which participants will implement their own MCMCs using R or Python (templates for both languages will be provided).

    After completion of the course, the participants will have gained a better understanding of how the main Bayesian methods implemented in many programs used in biological research work. Participants will also learn how to model at least basic problems using Bayesian statistics and how to implement the necessary algorithms to solve them.

    Participants are expected to have some knowledge of R or Python (each can choose their preferred language), but they will be guided "line-by-line" in writing their script. The aim is that, by the end of the week, each participant will have written their own MCMC – from scratch! Participants are encouraged to bring own datasets and questions and we will (try to) figure them out during the course and implement scripts to analyze them in a Bayesian framework.

    FOR MORE INFORMATION

    More information and registration at https://www.transmittingscience.com/courses/statistics-and-bioinformatics/introduction-bayesian-inference-practice/ or writing courses[at]transmittingscience.com

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