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Synopsis
A comprehensive overview of essential statistical concepts, useful statistical methods, data visualization, and modern computing tools for the climate sciences and many others such as geography and environmental engineering. It is an invaluable reference for students and researchers in climatology and its connected fields who wish to learn data science, statistics, R and Python programming. The examples and exercises in the book empower readers to work on real climate...
About the Authors
Samuel S. P. Shen is Distinguished Professor of Mathematics and Statistics at San Diego State University, and Visiting Research Mathematician at Scripps Institution of Oceanography, University of California, San Diego. Formerly, he was McCalla Professor of Mathematical and Statistical Sciences at the University of Alberta, Canada, and President of the Canadian Applied and Industrial Mathematics Society. He has held visiting positions at the NASA Goddard Space Flight...
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- PublisherCambridge University Press
- Publication date2024
- ISBN 10 1108842577
- ISBN 13 9781108842570
- BindingHardcover
- LanguageEnglish
- Number of pages458
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Statistics and Data Visualization in Climate Science with R and Python
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Statistics and Data Visualization in Climate Science With R and Python
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Statistics and Data Visualization in Climate Science with R and Python
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Statistics and Data Visualization in Climate Science With R and Python
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Statistics and Data Visualization in Climate with R and Python
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Statistics and Data Visualization in Climate Science with R and Python
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Statistics and Data Visualization in Climate Science with R and Python
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Statistics and Data Visualization in Climate with R and Python
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Statistics and Data Visualization in Climate Science with R and Python
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Statistics and Data Visualization in Climate Science with R and Python (Hardcover)
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Hardcover. Condition: new. Hardcover. A comprehensive overview of essential statistical concepts, useful statistical methods, data visualization, and modern computing tools for the climate sciences and many others such as geography and environmental engineering. It is an invaluable reference for students and researchers in climatology and its connected fields who wish to learn data science, statistics, R and Python programming. The examples and exercises in the book empower readers to work on real climate data from station observations, remote sensing and simulated results. For example, students can use R or Python code to read and plot the global warming data and the global precipitation data in netCDF, csv, txt, or JSON; and compute and interpret empirical orthogonal functions. The book's computer code and real-world data allow readers to fully utilize the modern computing technology and updated datasets. Online supplementary resources include R code and Python code, data files, figure files, tutorials, slides and sample syllabi. A comprehensive overview of essential statistical concepts, useful statistical methods, data visualization, and computing tools for the climate and related sciences. This book is an invaluable reference for students and researchers in climatology and its connected fields who wish to learn data science, statistics, R and Python programming. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Seller Inventory # 9781108842570
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