JASP is an open-source statistics program supported by the University of Amsterdam.

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Main Features


  • Frequentist analyses
  • Bayesian analyses

User-friendly Interface

  • Dynamic update of all results
  • Spreadsheet layout and an intuitive drag-and-drop interface
  • Progressive disclosure for increased understanding
  • Annotated output for communicating your results

Developed for publishing analyses

  • Integrated with The Open Science Framework (OSF)
  • Support for APA format (copy graphs and tables directly into Word)

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JASP Goals

Our main goal is to help statistical practitioners reach maximally informative conclusions with a minimum of fuss. This is why we have developed JASP, a cross-platform software program with a state-of-the-art graphical user interface. The JASP interface allows you to conduct statistical analyses in seconds, and without having to learn programming or risking a programming mistake.

JASP was designed with the user in mind: APA-formatted tables can be copy-pasted in your word processor, output can be extensively annotated, adjustment of input options dynamically changes the output, and selecting old output revives the associated input choices for inspection and adjustment. The core design principle in JASP is that default settings present simple analyses, with more complicated options available when needed. Unlike most other statistics programs, JASP does not attempt to “shock and awe” practitioners by presenting them with a smorgasbord of exotic analyses and a cornucopia of unstructured output. With JASP, you are able to see the forest for the trees.

JASP is open-source and free of charge, and we provide it as a service to the community. In turn, the community has offered valuable suggestions for improvement, either through social media, the JASP forum, or the JASP GitHub pages. We believe that proprietary statistical software often frustrates transparency and learning: with proprietary programs the code base cannot be inspected, the results cannot be reproduced by those who do not own a license, and students’ learning experience might be wasted when they are no longer able to afford the steep licensing costs.

JASP is statistically inclusive as it offers both frequentist and Bayesian analysis methods. Indeed, the primary motivation for JASP is to make it easier for statistical practitioners to conduct Bayesian analyses. We firmly believe that Bayesian statistics deserves to be applied more often and more widely than it is today, and that there is more to statistical inference than the frequentist p-value. A pragmatist may argue that –irrespective of one’s statistical convictions– it is prudent to report the results from both paradigms; when the results point in the same direction, this bolsters one’s confidence in the conclusions, but when the results are in blatant contradiction, this will weaken one’s confidence.

In the future we will continue to improve JASP by increasing its functionality, upgrading its interface, and expanding its documentation. Our core goals will not change, however, and we will strive to keep JASP friendly, free, and flexible. We hope you enjoy using JASP.

The JASP Team

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