Document Type
Article
Publication Title
International Journal of Open Source Software and Processes
Abstract
This paper discusses the definitions of open source software, free software and freeware, and the concept of big data. The authors then introduce R and Python as the two most popular open source statistical software (OSSS). Additional OSSS, such as JASP, PSPP, GRETL, SOFA Statistics, Octave, KNIME, and Scilab, are also introduced in this paper with function descriptions and modeling examples. They further discuss OSSS's capability in artificial intelligence application and modeling and Popular OSSS-based machine learning libraries and systems. The paper intends to provide a reference for readers to make proper selections of open source software when statistical analysis tasks are needed. In addition, working platform and selective numerical, descriptive and analysis examples are provided for each software. Readers could have a direct and in-depth understanding of each software and its functional highlights.
DOI
10.4018/IJOSSP.2021010101
Publication Date
2021
Recommended Citation
Niu, Gao; Segall, Richard S.; Zhao, Zichen; and Wu, Zhijian, "A Survey of Open Source Statistical Software (OSSS) and Their Data Processing Functionalities" (2021). Faculty Publications. 2.
https://arch.astate.edu/busn-isba-facpub/2
