JASP 0.12.0 has been released and is now available on our download page. DISCLAIMER: In developing this new version, we recently ran into a persistent bug on Macbooks containing an Intel Iris GPU. This bug can cause JASP to crash. We are working on a solution for this issue, so for Mac users with an Intel Iris GPU: please be…
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JASP 0.12 will offer important new functionality, including: Bayesian meta-analysis; Classical and Bayesian equivalence testing; Discover distributions; Visual modeling with Flexplot; and various additions to ANOVA. Also, JASP 0.12 offers improved annotation facilities, and our first language other than English — Dutch! (other languages will follow). Just set your language preference to Dutch, and the GUI, the output, and the…
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Over the past few years, we’ve found that mediation and moderation analysis are highly requested features. Since version 0.10.1, JASP can do both! This blogpost goes through two introductory examples, showing how mediation and moderation can be performed in JASP. Mediation means that the effect of a variable X on variable Y is (partially) indirect, through the variable M. Moderation…
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This blogpost provides an overview of the JASP tutorials available on YouTube. We will discuss the available tutorials and highlight some of the videos. First, the video’s by Erin Buchanan, professor in Cognitive Analytics at Harrisburg University of Science and Technology. Erin Buchanan owns the YouTube page ‘Statistics of DOOM’. The channel contains video tutorials for different statistical programs as…
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We are delighted to announce that registration is now open for the annual Amsterdam workshop on probabilistic modelling for cognitive science. The tenth installment of this workshop takes place August 17-21, 2020. Program In this workshop, plenary lectures provide the theoretical background of Bayesian statistics, and practical computer exercises teach participants how to use the popular JAGS and Stan programs…
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The JASP Team is excited to announce that registration for our annual two-day Amsterdam workshop is now open. The workshop takes place on August 24-25, 2020. Program In this two-day workshop, plenary lectures provide the theoretical background of Bayesian statistics and Bayesian hypothesis testing; in addition, practical exercises demonstrate how the JASP program is applied to a wide range of…
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One of the features that we have recently added to JASP is a Bayesian “A/B test”, that is, a test for the equality of two binomial proportions. This test is especially popular in the analysis of clinical trial data, where the proportion of medical successes (or failures) from a treatment group is contrasted against those from a control group. The…
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We’re excited to announce that we will be organizing two summer workshops in 2020. Similar to previous years, there will be one workshop focused on Bayesian cognitive modeling and one dedicated to Bayesian hypothesis testing in JASP. Unlike previous years, we will also feature Stan in our Bayesian cognitive modeling course! Have you always wanted to know the details of…
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The JASP team has organized many workshops to teach a broader audience about (Bayesian) statistics with JASP. There has been a lot of interest in the workshop materials and, of course, we are happy to share them. So far, we only responded to requests individually, but due to the growing interest we decided to put a collection of workshop materials…
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This post is a teaser for van den Bergh, D., van Doorn, J., Marsman, M., Draws, T., van Kesteren, E.-J., Derks, K., Dablander, F., Gronau, Q. F., Kucharsky, S., Komarlu Narendra Gupta, A. R., Sarafoglou, A., Voelkel, J. G., Stefan, A., Ly, A., Hinne, M., Matzke, D., & Wagenmakers, E.-J. (in press). A tutorial on conducting and interpreting a Bayesian…
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This is a continuation of our series on machine learning methods that have been implemented in JASP (version 0.11 onwards). In this blog post we train a machine learning model to find clusters within our data set. The goal of a clustering task is to detect structures in the data. To do so, the algorithm needs to (1)…
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