This Shiny App is designed to help users define their priors in a linear regression with two regression coefficients. Users are asked to specify their plausible parameter space and their expected prior means and uncertainty around these means. The PhD-delay example, which is used as example in most other tutorials on this website, has been used an easy-to-go introduction to Bayesian inference. In this example the linear and quadratic effect of age on PhD-delay are estimated. Users learn about the interaction between a linear and a quadratic effect in the same model, about how to think about plausible parameter spaces, and about specification of normally distributed priors for regression coefficients. More information about the data and the model can be found here.