This article discusses Bayesian inference in psychology, focusing on the application of JASP, an open-source statistical software package. JASP allows users to perform Bayesian hypothesis tests for standard statistical problems, including t-tests, ANOVA, correlation, regression, and contingency tables. The article outlines the philosophy behind JASP, emphasizing its user-friendly interface, open-source nature, and integration of both classical and Bayesian methods. It also presents five examples of Bayesian analyses conducted using JASP, including a correlation test for the height advantage of US presidents, a t-test for a kitchen roll rotation replication experiment, a one-way ANOVA for pain threshold and hair color, a two-way ANOVA for singers' height based on gender and pitch, and a two-way repeated measures ANOVA for hostility towards arthropods. The examples illustrate how JASP provides Bayesian results, including Bayes factors, posterior distributions, and credible intervals, and how these results can be interpreted. The article also discusses the advantages of Bayesian inference over classical methods, such as the ability to quantify evidence and update it as data come in, and the importance of open science practices in statistical analysis. The article concludes with a discussion of future developments for Bayesian analyses with JASP.This article discusses Bayesian inference in psychology, focusing on the application of JASP, an open-source statistical software package. JASP allows users to perform Bayesian hypothesis tests for standard statistical problems, including t-tests, ANOVA, correlation, regression, and contingency tables. The article outlines the philosophy behind JASP, emphasizing its user-friendly interface, open-source nature, and integration of both classical and Bayesian methods. It also presents five examples of Bayesian analyses conducted using JASP, including a correlation test for the height advantage of US presidents, a t-test for a kitchen roll rotation replication experiment, a one-way ANOVA for pain threshold and hair color, a two-way ANOVA for singers' height based on gender and pitch, and a two-way repeated measures ANOVA for hostility towards arthropods. The examples illustrate how JASP provides Bayesian results, including Bayes factors, posterior distributions, and credible intervals, and how these results can be interpreted. The article also discusses the advantages of Bayesian inference over classical methods, such as the ability to quantify evidence and update it as data come in, and the importance of open science practices in statistical analysis. The article concludes with a discussion of future developments for Bayesian analyses with JASP.