JASP: Graphical Statistical Software for Common Statistical Designs

By Jonathon Love, Ravi Selker, Maarten Marsman, Tahira Jamil, Damian Dropmann, Josine Verhagen, Alexander Ly, Quentin F. Gronau, Martin Šmı́ra, Sacha Epskamp and 6 more. Journal of Statistical Software, 2019

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This paper introduces JASP, a free graphical software package for basic statistical procedures such as t tests, ANOVAs, linear regression models, and analyses of contingency tables. JASP is open-source and differentiates itself from existing open-source solutions in two ways. First, JASP provides several innovations in user interface design; specifically, results are provided immediately as the user makes changes to options, output is attractive, minimalist, and designed around the principle of progressive disclosure, and analyses can be peer reviewed without requiring a "syntax". Second, JASP provides some of the recent developments in Bayesian hypothesis testing and Bayesian parameter estimation. The ease with which these relatively complex Bayesian techniques are available in JASP encourages their broader adoption and furthers a more inclusive statistical reporting practice. The JASP analyses are implemented in R and a series of R packages.

Subfields: Statistics and Probability

View Paper: https://www.semanticscholar.org/paper/69ba44956f8a605907e7b99bba7f197cd426dbb1

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