Introducing JASP

Released this week, JASP version brings a number of improvements. For data visualization, the most prominent advance is the extension of the “split-by” functionality (courtesy of JASP team member Erik-Jan van Kesteren). To demonstrate how it works, we plot data from a study conducted at the University of Melbourne in the 1970s, examining the possible relation between hair color and pain threshold (McClave & Dietrich, 1991, Exercise 10.20). The data contain estimates of pain tolerance for participants of four different hair colors: dark brunette, light brunette, dark blond, and light blond.

After opening the data file we navigate to Descriptives > Descriptive Statistics and find the new “split-by” option below the Variables box.

In the previous version of JASP we could only obtain descriptive statistics collapsed over all four hair colors. To illustrate, we move “Pain Tolerance” to Variables and find the following table:

Clearly, this table does not provide useful information about the differences between hair colors. The “split” functionality overcomes this limitation. We move “Hair Color” to Split, and then obtain a more informative table:

The numbers in this table suggest that pain tolerance differs between the four hair colors. Dark brunettes have a mean tolerance of 37.4, while light blondes score much higher with a mean threshold of 59.2. In addition to producing more informative tables, the split option works for every type of plot in the Descriptive Statistics analysis. As an example, we first create a boxplot without the split option:

And with the split option:

We hope you enjoy this new feature and all the other improvements that this version of JASP has to offer.


McClave, J. T., & Dietrich, F. H. II. (1991). Statistics. San Francisco: Dellen Publishing.

Like this post?

Subscribe to our newsletter to receive regular updates about JASP including our latest blog posts, JASP articles, example analyses, new features, interviews with team members, and more! You can unsubscribe at any time.

About the author

Tim de Jong

Tim de Jong is a graduate student at the University of Amsterdam. At JASP, he is responsible for improving the R analyses and enriching the Bayesian ANOVA and t-tests.