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  1. ISBN 978-1-4039-1800-0. Renfro, Charles G. (2004). Computational Econometrics: Its Impact on the Development of Quantitative Economics. IOS Press. ISBN 1-58603-426-X. Zhu, Xiaoping; Kuljaca, Ognjen (2005). "A Short Preview of Free Statistical Software Packages for Teaching Statistics to Industrial Technology Majors" (PDF).

  2. Rguroo Statistical Software - An online statistical software designed for teaching and analyzing data. S-PLUS – general statistics package. SAS (software) – comprehensive statistical package. SHAZAM (Econometrics and Statistics Software) – comprehensive econometrics and statistics package.

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  4. en.wikipedia.org › wiki › R_packageR package - Wikipedia

    R packages are extensions to the R statistical programming language. R packages contain code, data, and documentation in a standardised collection format that can be installed by users of R, typically via a centralised software repository such as CRAN (the Comprehensive R Archive Network).

  5. R is a programming language for statistical computing and data visualization. It has been adopted in the fields of data mining, bioinformatics, and data analysis. The core R language is augmented by a large number of extension packages, containing reusable R .

  6. en.wikipedia.org › wiki › JASPJASP - Wikipedia

    JASP (Jeffreys’s Amazing Statistics Program) is a free and open-source program for statistical analysis supported by the University of Amsterdam. It is designed to be easy to use, and familiar to users of SPSS .

  7. en.wikipedia.org › wiki › SPSSSPSS - Wikipedia

    SPSS Statistics is a statistical software suite developed by IBM for data management, advanced analytics, multivariate analysis, business intelligence, and criminal investigation. Long produced by SPSS Inc., it was acquired by IBM in 2009. Versions of the software released since 2015 have the brand name IBM SPSS Statistics .

  8. en.wikipedia.org › wiki › JamoviJamovi - Wikipedia

    jamovi is an open source graphical user interface for the R programming language. [4] It is used in statistical research, especially as a tool for ANOVA (analysis of variance) and to understand statistical inference. [5] [6] It also can be used for linear regression, [7] mixed models and Bayesian models. [8]