JASP: Open-source Statistics (Free app)

JASP aims to be a complete statistical package for both Bayesian and Frequentist statistical methods, that is easy to use and familiar to users of SPSS

JASP is an easy-to-use statistical analysis software, Its the perfect choice for beginners and students. JASP has installable packages for Windows, MacOSX, and Linux. It can run on the cloud as well using RollApp which is a platform for running the desktop application in the cloud. In addition to JASP format *.jasp, JASP reads multiple data file formats including .sav, .txt, .csv, and .ods.

JASP was released as an open-source project under GPLv3.0 and it's supported by the University of Amsterdam, JASP team has released get started tutorial, while How to use JASP" is full of blog tutorials, videos and GIF images for JASP functionalities.

Supported formats

JASP currently reads the following formats: .sav, .txt, .csv, .ods, .tsv, .dta, .por, .sas7bdat, .sas7bcat, and of course the .jasp format.

Included modules

  • Descriptives
  • T-Tests
  • ANOVA
  • Mixed Models
  • Regression
  • Frequencies
  • Factor
  • Acceptance Sampling
  • Audit
  • Bain
  • BSTS
  • Circular Statistics
  • Cochrane Meta-Analyses
  • Distributions
  • Equivalence T-Tests
  • JAGS
  • Learn Bayes
  • Machine Learning
  • Meta-Analysis
  • Network
  • Power
  • Quality Control
  • Prophet
  • Reliability
  • Structural Equation Modeling (SEM)
  • Summary Statistics
  • Visual Modeling

License

JASP is made up of two parts, or executables. The JASP graphical user interface, and the JASP engine responsible for running the analyses in the background.

  • As an executable binary, the JASP graphical user interface is released under the GNU Affero General Public License, version 3
  • As an executable binary, the JASP engine is released under the GNU General Public License, version 2

The JASP source code itself is licensed:

  • Common: GPL2+
  • Engine: GPL2+
  • Desktop: AGPL3+

Platforms

macOS Windows, Linux

License

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Tags

statistics,math,analysis,data analysis,statistical analysis,science,spss,spss alternative

Resources

Github