[ONLINE]- Intro to Bayesian Statistics in R
Details
Hi, everybody!
We are super excited to have Angelika Stefan with us PhD candidate at the Psychological Methods department at the University of Amsterdam, - sharing her knowledge with us Bayesian statistics with R!
DESCRIPTION
Bayesian data analysis presents an attractive alternative to p-value hypothesis testing. In the past years, Bayesian methods have become increasingly popular because they provide several advantages to the applied researcher, such as the ability to quantify evidence and successively update it as data come in.
In this workshop, I will give an introduction to the basic concepts of Bayesian statistics, such as the prior distribution, the posterior distribution, and the Bayes factor. After a brief conceptual introduction, we will fit a simple Bayesian model using just Base-R. I will finish the workshop by giving an outlook to more complex models, and present R-packages that can be used for advanced hypothesis testing and parameter estimation in the Bayesian framework.
ABOUT ANGELIKA
I am a PhD student in the Psychological Methods department at the University of Amsterdam. My research mostly focuses on subjective Bayesian methods and experimental design planning; that is, I investigate statistical methods that can make research in psychology more efficient and allow researchers to incorporate existing knowledge into their models. I am a member of the JASP team and a co-founder of the ReproducibiliTea Amsterdam chapter. I am passionate about making science and statistics accessible to everyone, and have given various workshops about Bayesian statistics and Open Science in the past.