Published by the Foundation for Open Access Statistics Editors-in-chief: Bettina Grün, Torsten Hothorn, Rebecca Killick, Edzer Pebesma, Achim Zeileis    ISSN 1548-7660; CODEN JSSOBK
Authors: Jonathon Love, Ravi Selker, Maarten Marsman, Tahira Jamil, Damian Dropmann, Josine Verhagen, Alexander Ly, Quentin F. Gronau, Martin Šmíra, Sacha Epskamp, Dora Matzke, Anneliese Wild, Patrick Knight, Jeffrey N. Rouder, Richard D. Morey, Eric-Jan Wagenmakers
Title: JASP: Graphical Statistical Software for Common Statistical Designs
Abstract: 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.

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Paper: JASP: Graphical Statistical Software for Common Statistical Designs     Download PDF (Downloads: 3709)
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DOI: 10.18637/jss.v088.i02

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Paper: Creative Commons Attribution 3.0 Unported License
Code: GNU General Public License (at least one of version 2 or version 3) or a GPL-compatible license.