Applied Data Analysis and Modeling for Energy Engineers and Scientists

Nonfiction, Science & Nature, Science, Physics, Thermodynamics, Technology, Power Resources
Cover of the book Applied Data Analysis and Modeling for Energy Engineers and Scientists by T. Agami Reddy, Springer US
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Author: T. Agami Reddy ISBN: 9781441996138
Publisher: Springer US Publication: August 9, 2011
Imprint: Springer Language: English
Author: T. Agami Reddy
ISBN: 9781441996138
Publisher: Springer US
Publication: August 9, 2011
Imprint: Springer
Language: English

Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and confidence to work in data analysis and modeling. This volume uses numerous solved examples, published case studies from the author’s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the “processes”along with the tools.

View on Amazon View on AbeBooks View on Kobo View on B.Depository View on eBay View on Walmart

Applied Data Analysis and Modeling for Energy Engineers and Scientists fills an identified gap in engineering and science education and practice for both students and practitioners. It demonstrates how to apply concepts and methods learned in disparate courses such as mathematical modeling, probability,statistics, experimental design, regression, model building, optimization, risk analysis and decision-making to actual engineering processes and systems. The text provides a formal structure that offers a basic, broad and unified perspective,while imparting the knowledge, skills and confidence to work in data analysis and modeling. This volume uses numerous solved examples, published case studies from the author’s own research, and well-conceived problems in order to enhance comprehension levels among readers and their understanding of the “processes”along with the tools.

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