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Introduction to the Popular Open Source Statistical Software (OSSS)

Introduction to the Popular Open Source Statistical Software (OSSS)
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Author(s): Zhijian Wu (New York University, USA), Zichen Zhao (Yale University, USA)and Gao Niu (Bryant University, USA)
Copyright: 2021
Pages: 35
Source title: Research Anthology on Usage and Development of Open Source Software
Source Author(s)/Editor(s): Information Resources Management Association (USA)
DOI: 10.4018/978-1-7998-9158-1.ch040

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Abstract

This chapter first introduces the two most popular Open Source Statistical Software (OSSS), R and Python, along with their Integrated Development Environment (IDE) and Graphical User Interface (GUI). Secondly, additional OSSS, such as JASP, PSPP, GRETL, SOFA Statistics, Octave, KNIME, and Scilab, will also be introduced in this chapter with function descriptions and modeling examples. The chapter intends to create a reference for readers to make proper selection of the Open Source Software when a statistical analysis task is in demand. The chapter describes software explicitly in words. 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.

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