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  • 标题:JASP: Graphical Statistical Software for Common Statistical Designs
  • 本地全文:下载
  • 作者:Jonathon Love ; Ravi Selker ; Maarten Marsman
  • 期刊名称:Journal of Statistical Software
  • 印刷版ISSN:1548-7660
  • 电子版ISSN:1548-7660
  • 出版年度:2019
  • 卷号:88
  • 期号:1
  • 页码:1-17
  • DOI:10.18637/jss.v088.i02
  • 出版社:University of California, Los Angeles
  • 摘要: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.
  • 关键词:JASP; statistical software; Bayesian inference; graphical user interface; basic statistics.
  • 其他关键词:JASP;statistical software;Bayesian inference;graphical user interface;basic statistics
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