Bayesian Statistics in JASP
For a long time, Bayesian statistics has been overlooked in the training of quantitative methods, but it is taking on a leading role in empirical research in many fields of science as the Bayesian approach provides a flexible, powerful alternative to frequentist or classical statistics. Although most software tools are capable of computing a wide range of tests and models from a Bayesian perspective, the core principles of Bayesian statistics are not always trivial to grasp.
The purpose of this workshop is to familiarize participants with the core concepts of Bayesian statistics, both from a philosophical and mathematical perspective. Several examples will be used to illustrate how to compute, report, and interpret Bayesian hypothesis tests for popular statistical models such as binomial tests, correlations, t-tests, analysis of variance or linear regressions in JASP - a program whose attractive graphical user interface allows us to focus on core Bayesian concepts and principles, unburdened by the need to explain the detailed workings of highly specialized software programs.
No specific mathematical expertise is required, but familiarity with statistical methods such as t-tests or linear regressions can be helpful. The workshop will be held in English.
Advanced bachelor and master students from all fields of study; Participation of doctoral candidates and faculty members is only possible if vacancies remain at the end of the registration period.