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Comparative Approaches to Using R and Python for Statistical Data Analysis

Comparative Approaches to Using R and Python for Statistical Data Analysis

Copyright: © 2017 |Pages: 197
ISBN13: 9781683180166|ISBN10: 168318016X|EISBN13: 9781522519898
DOI: 10.4018/978-1-68318-016-6
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MLA

Sarmento, Rui, and Vera Costa. Comparative Approaches to Using R and Python for Statistical Data Analysis. IGI Global, 2017. https://doi.org/10.4018/978-1-68318-016-6

APA

Sarmento, R. & Costa, V. (2017). Comparative Approaches to Using R and Python for Statistical Data Analysis. IGI Global. https://doi.org/10.4018/978-1-68318-016-6

Chicago

Sarmento, Rui, and Vera Costa. Comparative Approaches to Using R and Python for Statistical Data Analysis. Hershey, PA: IGI Global, 2017. https://doi.org/10.4018/978-1-68318-016-6

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The application of statistics has proliferated in recent years and has become increasingly relevant across numerous fields of study. With the advent of new technologies, its availability has opened into a wider range of users.

Comparative Approaches to Using R and Python for Statistical Data Analysis is a comprehensive source of emerging research and perspectives on the latest computer software and available languages for the visualization of statistical data. By providing insights on relevant topics, such as inference, factor analysis, and linear regression, this publication is ideally designed for professionals, researchers, academics, graduate students, and practitioners interested in the optimization of statistical data analysis.

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Front Materials
Title Page
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Copyright Page
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Advances in Systems Analysis, Software Engineering, and High Performance Computing (ASASEHPC) Book Series
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Dedication
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Preface
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Introduction
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Chapters
Back Materials
About the Authors
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Index
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