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Introduction to the Popular Open Source Statistical Software (OSSS)

Introduction to the Popular Open Source Statistical Software (OSSS)

Zhijian Wu, Zichen Zhao, Gao Niu
Copyright: © 2020 |Pages: 38
ISBN13: 9781799827689|ISBN10: 1799827682|ISBN13 Softcover: 9781799827696|EISBN13: 9781799827702
DOI: 10.4018/978-1-7998-2768-9.ch003
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MLA

Wu, Zhijian, et al. "Introduction to the Popular Open Source Statistical Software (OSSS)." Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities, edited by Richard S. Segall and Gao Niu, IGI Global, 2020, pp. 73-110. https://doi.org/10.4018/978-1-7998-2768-9.ch003

APA

Wu, Z., Zhao, Z., & Niu, G. (2020). Introduction to the Popular Open Source Statistical Software (OSSS). In R. Segall & G. Niu (Eds.), Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities (pp. 73-110). IGI Global. https://doi.org/10.4018/978-1-7998-2768-9.ch003

Chicago

Wu, Zhijian, Zichen Zhao, and Gao Niu. "Introduction to the Popular Open Source Statistical Software (OSSS)." In Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities, edited by Richard S. Segall and Gao Niu, 73-110. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-2768-9.ch003

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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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