Re: [DMG] Digest for dinosaurmailinggroup@googlegroups.com - 1 update in 1 topic

[Paul P]

Hi Sole,
Just wondering if you've ever considered holding some classes in the evening..? 13:00 Madrid time is 04:00 California time (9 hr time difference), so this class is not an option for me, or for most people here.

Many people like evening classes, even when they're actually in the evening. Especially in Europe, no? Just a thought.

   Paul P.


On Wednesday, January 22, 2025, <dinosaurma...@googlegroups.com> wrote:
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> Course live online Intro Bayesian Analysis, February 17th-21st, 2025 - 1 Update
>
> Course live online Intro Bayesian Analysis, February 17th-21st, 2025
> Soledad De Esteban Trivigno <soledad.de.es...@gmail.com>: Jan 22 11:15AM -0800
>
> Dear colleagues,
>  
> Registration is open for the course "Introduction to Bayesian Inference in
> Practice". This course will be held live online (synchronous). Max 18
> participants.
>  
> Dates: February 17th-21st, 2025, from 13:00 to 17:00 (Madrid time zone).
>  
> Instructors: Dr. Daniele Silvestro
> <https://www.transmittingscience.com/instructors/daniele-silvestro/> (University
> of Gothenburg, Sweden) and Tobias Andermann
> <https://www.transmittingscience.com/instructors/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.
>  
> More information and registration at
> https://www.transmittingscience.com/courses/statistics-and-bioinformatics/introduction-bayesian-inference-practice/
> or writing cou...@transmittingscience.com
>  
> Best regards
>  
> Sole
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