text: 368,59,1239497859147456518,1066288106,Fabian Dablander,"New paper! We derive default Bayes factors for testing hypotheses on independent population variances: <LINK> @donvdbergh @AlexanderLyNL @EJWagenmakers (1/6) <LINK> We choose a prior so that the resulting Bayes factor fulfills a number of desiderata. This leads to a closed-form expression for the K = 1 and K = 2 group case. (2/6) <LINK> It is arguably more intuitive to reason about standard deviations than about variances, and we provide practical examples from psychology and paleoanthropology (cool, right?). One may also elicit an informative prior rather than rely on defaults. <LINK> We extend out Bayes factor to K &gt; 2 groups and allow testing 'mixed' or 'informative' hypothesis (see left image). We provide practical examples from archeology (chupa pots!) and education. <LINK> Our default Bayes factor generalizes a recently proposed automatic fractional Bayes factor (Böing-Messing & Mulder, 2018), yielding the exact same results when testing hypotheses about (in)equality when choosing a rather wide prior \alpha = 0.50. <LINK> All of this is implemented in the R package 'bfvartest', which is available from Github (<LINK>). Give it a go! Of course, this will also be implemented in @JASPStats for ease of use :-) <LINK>",https://arxiv.org/abs/2003.06278,"Testing the (in)equality of variances is an important problem in many statistical applications. We develop default Bayes factor tests to assess the (in)equality of two or more population variances, as well as a test for whether the population variance equals a specific value. The resulting test can be used to check assumptions for commonly used procedures such as the $t$-test or ANOVA, or test substantive hypotheses concerning variances directly. We further extend the Bayes factor to allow $\mathcal{H}_0$ to have a null-region. Researchers may have directed hypotheses such as $\sigma_1^2 > \sigma_2^2$, or want to combine hypotheses about equality with hypotheses about inequality, for example $\sigma_1^2 = \sigma_2^2 > (\sigma_3^2, \sigma_4^2)$. We generalize our Bayes factor to accommodate such hypotheses for $K > 2$ groups. We show that our Bayes factor fulfills a number of desiderata, provide practical examples illustrating the method, and compare it to a recently proposed fractional Bayes factor procedure by B\""oing-Messing & Mulder (2018). Our procedure is implemented in the R package $bfvartest$. ","Default Bayes Factors for Testing the (In)equality of Several Population