9781470448691-1470448696-Modeling and Data Analysis: An Introduction With Environmental Applications

Modeling and Data Analysis: An Introduction With Environmental Applications

ISBN-13: 9781470448691
ISBN-10: 1470448696
Author: John B. Little
Publication date: 2019
Publisher: American Mathematical Society
Format: Hardcover 323 pages
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Book details

ISBN-13: 9781470448691
ISBN-10: 1470448696
Author: John B. Little
Publication date: 2019
Publisher: American Mathematical Society
Format: Hardcover 323 pages

Summary

Acknowledged author John B. Little wrote Modeling and Data Analysis: An Introduction With Environmental Applications comprising 323 pages back in 2019. Textbook and eTextbook are published under ISBN 1470448696 and 9781470448691. Since then Modeling and Data Analysis: An Introduction With Environmental Applications textbook was available to sell back to BooksRun online for the top buyback price or rent at the marketplace.

Description

Can we coexist with the other life forms that have evolved on this planet? Are there realistic alternatives to fossil fuels that would sustainably provide for human society's energy needs and have fewer harmful effects? How do we deal with threats such as emergent diseases? Mathematical models equations of various sorts capturing relationships between variables involved in a complex situation are fundamental for understanding the potential consequences of choices we make. Extracting insights from the vast amounts of data we are able to collect requires analysis methods and statistical reasoning. This book on elementary topics in mathematical modeling and data analysis is intended for an undergraduate liberal arts mathematics -type course but with a specific focus on environmental applications. It is suitable for introductory courses with no prerequisites beyond high school mathematics. A great variety of exercises extends the discussions of the main text to new situations and/or introduces new real-world examples. Every chapter ends with a section of problems, as well as with an extended chapter project which often involves substantial computing work either in spreadsheet software or in the R statistical package.

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