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Registration is open for Transmitting Science course “Introduction to Bayesian Inference in Practice”, May 6th-10th, 2019, Barcelona (Spain). Instructors: Dr. Daniele Silvestro (University of Gothenburg, Sweden) and Tobias Hofmann (University of Gothenburg, Sweden) Course overview Bayesian methods have become standard practice in several fields, (e.g. phylogenetic inference, evolutionary (paleo)biology, genomics), yet understanding how this Bayesian machinery works is not always trivial. 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. 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 encouraged to think of potential applications of Bayesian inference in their research, which we will discuss and try to implement during the course. For more information please check the course webpage: http://www.transmittingscience.org/courses/statistics-and-bioinformatics/introduction-bayesian-inference-practice/
Agency: PR statistics Location: Glasgow Scotland Course cost: £520 Dates: 10/15/2018-10/19/2018 https://www.prstatistics.com/ Applied Bayesian modelling for ecologists and epidemiologists (ABME04) This course will be delivered by Matt Denwood in Glasgow City Centre from 15th - 19th October 2018. https://www.prstatistics.com/course/applied-bayesian-modelling-for-ecologists-and-epidemiologists-abme04/ Please feel free to share anywhere you see fit. Course Overview: This application-driven course will provide a founding in the basic theory & practice of Bayesian statistics, with a focus on MCMC modeling for ecological & epidemiological problems. Starting from a refresher on probability & likelihood, the course will take students all the way to cutting-edge applications such as state-space population modelling & spatial point-process modelling and will be of interest to anyone studying population ecology of marine mammals. By the end of the week, you should have a basic understanding of how common MCMC samplers work and how to program them, and have practical experience with the BUGS language for common ecological and epidemiological models. The experience gained will be a sufficient foundation enabling you to understand current papers using Bayesian methods, carry out simple Bayesian analyses on your own data and springboard into more elaborate applications such as dynamical, spatial and hierarchical modelling. Intended Audience: Research postgraduates, practicing academics and primary investigators in ecology and epidemiology and professionals in government and industry. Oliver Hooker +44 (0) 7966500340 firstname.lastname@example.org