Category Archives: Uncategorized

Please help: BayesFactor testimonials

I’m compiling a portfolio about the BayesFactor software, and I would love to have short comments (a few sentences to a paragraph) from people who have found the software useful. If you have used the software and you wouldn’t mind sending me a short blurb about your experience, I’d love to hear from you! Please send your BayesFactor testimonial to richarddmorey@gmail.com. Thanks in advance!

Call for papers: Bayesian statistics, at Zeitschrift für Psychologie

I am guest editing a special topical issue of Zeitschrift für Psychologie on Bayesian statistics. The complete call, with details, can be found here: [pdf]. Briefly:

As Bayesian statistics become part of standard analysis in psychology, the Zeitschrift für Psychologie invites papers to a topical issue highlighting Bayesian methods. We invite papers on a broad range of topics, including the benefits and limitations of Bayesian approaches to statistical inference, practical benefits of Bayesian methodologies, interesting applications of Bayesian statistics in psychology, and papers related to statistical education of psychologists from a Bayesian perspective. In addition to suggestions for full original or review articles, shorter research notes and opinion papers are also welcome. 

We invite scholars from various areas of scholarship, including but not limited to psychology, statistics, philosophy, and mathematics, to submit their abstracts on potential papers.

Abstracts are due at the end of July. Critiques and articles about the history of Bayesian statistics are also welcome.

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Visualizing statistical distributions with javascript

For the past few years, I’ve been developing and using a library I created that allows me to easily generate visualizations of statistical distributions for teaching. One can specify a distribution along with a parametrization, and the library sees it and generates a table containing all the distributions, which gives links to interactive plots that allow anyone to see how changing the parameters affects the distribution. In addition, clicking on the plot allows finding areas under the distribution. Users can switch between PDF and CDF views. I’ve now opened the code on github.

You can also link directly to a visualization using URL parameters. For instance:

http://learnbayes.org/demo/stat-distributions-js/distributionDisplay.html?dist=normal&ptzn=2&plotxrng=50,150&rangesLo=50,3&rangesHi=150,45&starts=100,15

See the live demo and the github repository for more details.

Example screenshots: