Q. How Data Editing works?

A. When you double-click the data on JASP, it will open the data file with the default editor associated with the extension of your data file (csv, sav, ods, etc…). This can be Excel, SPSS, LibreOffice… Be careful: a csv file can be associated with JASP itself, making opening JASP again when you click on the data! You can change this behaviour with your operating system. Here is a link for Windows or for Mac. You can also oblige JASP to open another editor by specifying it in the preferences menu (in the top-right icon). You can even ask to open notepad or vi! When your editor is opened with your data, if you save your changes with your editor, JASP will automatically notice it, refresh the data, and if needed rerun your analyses.
In this way, you edit the data with your preferred editor, and JASP loads smoothly your changes.
As JASP support ODS file, you can add any functions to manipulate your data, and these manipulations will be automatically detected by JASP.
If you click on the File menu, you can see the Sync Data sub-menu: here you can see and specify which file JASP uses to synchronise with.


Q. How Label Editing works?

A. If you click on a column header, you can either change the measurement level of the column (by click the icon), or change the labels of the column (by clicking the name). In the latter case, a window open that shows the values and labels of that column. You may edit the label by double-clicking it. You may also change the order of the labels by clicking on the up, down or reverse button. Your changes are directly processed by JASP in the analyses.
This video shows you more details.


Q. How do I cite JASP?

A. One of the best ways that you can support the JASP project is by citing it. Citations are an important measure of how widely software is used, and an important indicator to funding bodies of JASP’s relevance. At present, there are no publications you can cite for JASP (there are several in the pipeline, however!). For now, we suggest you use:

To cite JASP in publications use:

JASP Team (2017). JASP (Version[Computer software].

And the BibTeX entry :

AUTHOR =  {{JASP Team}, {The}},
TITLE =        {{JASP (Version[Computer software]}},
YEAR =         {2017},
URL =           {https://jasp-stats.org/}


Q. What are the long-term prospects for JASP?

A. Currently, JASP is supported by several grants and a team of motivated software developers, academics, and students. Our lead software developer and several core team members have tenured positions. The Psychological Methods Group at the University of Amsterdam is dedicated to long-term support for JASP. Finally, the JASP code is open-source and will always remain freely available online. In sum, JASP is here to stay.


Q. Will JASP always be free?

A. Yes — More importantly, it is released under an Open Source license, which means that even if we turn evil, we will not be able to take JASP away or prevent others from contributing to it, working on it, or distributing it freely. This excerpt from our license sums it up nicely:

The licenses for most software and other practical works are designed to take away your freedom to share and change the works. By contrast, our General Public Licenses are intended to guarantee your freedom to share and change all versions of a program — to make sure it remains free software for all its users.


Q. What license is JASP released under?

A. The GNU Affero General Public License, Version 3


Q. What programming language is JASP written in?

A. The JASP application is written in C++, using the Qt toolkit. The analyses themselves are written in either R or C++ (python support will be added soon!). The display layer (where the tables are rendered) is written in javascript, and is built on top of jQuery UI and webkit.


Q. If JASP uses R for doing analyses, is it possible to export the R code which was used for that analysis?

A. Kinda. The R code for the analyses is available on Github here.

A lot of people imagine that JASP writes a script file out for each analysis, and then runs that script file – the same way that someone using R interactively would. In which case it would be easy to export the script file. In practice, of course, it doesn’t work like this. Each analysis is represented by a single function, and each function is in the R file on github.