BEGIN:VCALENDAR VERSION:2.0 PRODID:icalendar-ruby CALSCALE:GREGORIAN BEGIN:VEVENT DTSTAMP:20260710T224500Z UID:06c8fdf7-f7be-47f9-9e38-6526da0fbed4 DTSTART:20240513T090000Z DTEND:20240514T170000Z DESCRIPTION:# Overview\nData analysis is fundamental for arriving at scient ific conclusions and testing different model hypotheses. Key to this is un derstanding uncertainty in our results\, and Bayesian statistics offers a framework to quantify and assess the variability in our inference from dat a. This 2-day course will introduce participants to the core concepts of B ayesian statistics through lectures and practical exercises. The exercise s will be implemented in the widely used R programming language and the Rs tan library. They will enable participants to use standard Bayesian statis tical tools and interpret their results. \n\n\n\n# Schedule \n## Day 1 \n9 :00 – 17:00: **Jack Kuipers** (ETH Zurich and SIB) and **Wandrille Duche min** (University of Basel and SIB) \n* T-test recap\n* P-values and confi dence intervals\n* Monte Carlo methods\n* Bayesian first steps\n\n\n## Day 2 \n9:00 – 17:00: **Jack Kuipers** (ETH Zurich and SIB) and **Wandrille Duchemin** (University of Basel and SIB) \n* Bayesian t-tests (STAN + BRM S)\n* Priors\n* Bayesian linear regression\n* Bayesian logistic regression \n \n\n# Audience\nThis course is intended for life scientists familiar wi th statistical inference and who would like to add the Bayesian perspectiv e to enrich their research. \n\n# Learning outcomes\nAt the end of the co urse\, participants should be able to: \n* Recognise the core components o f a Bayesian model \n* List the main concepts of methods for Bayesian infe rence \n* Implement a simple Bayesian model in R \n* Interpret the results of a Bayesian model \n\n# Prerequisites\n##### Knowledge / competencies\n **Being at ease with R is absolutely required for this course** (at least equivalent to the [First steps with R](https://github.com/sib-swiss/first- steps-with-R-training) SIB course). Basic knowledge of statistical inferen ce (for instance\, equivalent to the [Introduction to statistics](https:// www.sib.swiss/training/course/20220207_STATR) SIB course) is also required . \n \nBoth pre-requisites are also taught by the ETHZurich course [introd uction to statistics and R](http://www.vvz.ethz.ch/Vorlesungsverzeichnis/l erneinheit.view?semkez=2022W&\;ansicht=KATALOGDATEN&\;lerneinheitId= 163598&\;lang=en) \n\n##### Technical\nYou are required to bring your o wn laptop and make sure that the following software is installed PRIOR to the course: \n* A recent verion of [R](https://www.r-project.org/) and [R Studio](https://www.rstudio.com/products/rstudio/download/) (the free vers ion is more than enough).\n\nAdditionally\, make sure to have the followin g R libraries installed: \n* The [Rstan](https://github.com/stan-dev/rstan /wiki/RStan-Getting-Started) package (warning\, there are 2 steps to the i nstallation: Configuring C++ toolchains\, and then installation of Rstan) \n* [Rmarkdown](https://rmarkdown.rstudio.com/lesson-1.html) \n* [Shiny](h ttps://shiny.rstudio.com/tutorial/written-tutorial/lesson1/) \n* [tidyvers e](https://www.tidyverse.org/packages/) \n* [BRMS](https://cran.r-project. org/web/packages/brms/index.html) \n\n\n# Application\nThe registration fe es for academics are **200 CHF** and **1000 CHF** for for-profit companies . \n\nWhile participants are registered on a first come\, first served bas is\, exceptions may be made to ensure diversity and equity\, which may inc rease the time before your registration is confirmed.\n\nYou will be infor med by email of your registration confirmation. Upon reception of the conf irmation email\, participants will be asked to confirm attendance by payin g the fees within 5 days.\n\nApplications close on **22/04/2024** or as so on as the course is full. Deadline for free-of-charge cancellation is set to **29/04/2024**. Cancellation after this date will not be reimbursed. Pl ease note that participation in SIB courses is subject to our [general con ditions](https://www.sib.swiss/training/terms-and-conditions).\n\n# Venue and Time\nThis course will be in Basel\, in the Kollegianhaus building of the University of Basel.\n\nThe course will start at 9:00 and end around 1 7:00. \n\nMore information will be provided to the registered participants one week before the course starts. \n\n# Additional information\nCoordin ation: Patricia Palagi\n\nWe will recommend 0.5 ECTS credits for this cour se (given that a successful evaluation is achieved at the end of the cours e).\n\nYou are welcome to register to the SIB courses mailing list to be i nformed of all future courses and workshops\, as well as all important dea dlines using the form [here](https://lists.sib.swiss/mailman/listinfo/cour ses).\n\nPlease note that participation in SIB courses is subject to our [ general conditions](https://www.sib.swiss/training/terms-and-conditions).\ n\nSIB abides by the [ELIXIR Code of Conduct](https://elixir-europe.org/ev ents/code-of-conduct). Participants of SIB courses are also required to ab ide by the same code.\n\nFor more information\, please contact [training@s ib.swiss](mailto://training@sib.swiss). SUMMARY:Introduction to Bayesian Statistics with R URL;VALUE=URI:https://www.sib.swiss/training/course/20240513_IBAYE END:VEVENT END:VCALENDAR