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Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities

Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities

Copyright: © 2020 |Pages: 237
ISBN13: 9781799827689|ISBN10: 1799827682|EISBN13: 9781799827702
DOI: 10.4018/978-1-7998-2768-9
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MLA

Segall, Richard S., and Gao Niu, editors. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities. IGI Global, 2020. https://doi.org/10.4018/978-1-7998-2768-9

APA

Segall, R. S. & Niu, G. (Eds.). (2020). Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities. IGI Global. https://doi.org/10.4018/978-1-7998-2768-9

Chicago

Segall, Richard S., and Gao Niu, eds. Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-2768-9

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With the development of computing technologies in today’s modernized world, software packages have become easily accessible. Open source software, specifically, is a popular method for solving certain issues in the field of computer science. One key challenge is analyzing big data due to the high amounts that organizations are processing. Researchers and professionals need research on the foundations of open source software programs and how they can successfully analyze statistical data.

Open Source Software for Statistical Analysis of Big Data: Emerging Research and Opportunities provides emerging research exploring the theoretical and practical aspects of cost-free software possibilities for applications within data analysis and statistics with a specific focus on R and Python. Featuring coverage on a broad range of topics such as cluster analysis, time series forecasting, and machine learning, this book is ideally designed for researchers, developers, practitioners, engineers, academicians, scholars, and students who want to more fully understand in a brief and concise format the realm and technologies of open source software for big data and how it has been used to solve large-scale research problems in a multitude of disciplines.

Table of Contents

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Front Materials
Title Page
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Copyright Page
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Advances in Computer and Electrical Engineering (ACEE) Book Series
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Editorial Advisory Board and List of Reviewers
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Preface
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Acknowledgment
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Chapters
Back Materials
Conclusion
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Related Readings
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About the Contributors
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Index
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