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Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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PAP. Condition: New. New Book. Shipped from UK. Established seller since 2000.
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Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Language: English
Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Published by Oxford University Press, Oxford, 2022
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Paperback. Condition: new. Paperback. Random process analysis (RPA) is used as a mathematical model in physics, chemistry, biology, computer science, information theory, economics, environmental science, and many other disciplines. Over time, it has become more and more important for the provision of computer code and data sets. This book presents the key concepts, theory, and computer code written in R, helping readers with limited initial knowledge of random processes to become confident in their understanding and application of these principles in their own research. Consistent with modern trends in university education, the authors make readers active learners with hands-on computer experiments in R code directing them through RPA methods and helping them understand the underlying logic.Each subject is illustrated with real data collected in experiments performed by the authors or taken from key literature. As a result, the reader can promptly apply the analysis to their own data, making this book an invaluable resource for undergraduate and graduate students, as well as professionals, in physics, engineering, biophysical and environmental sciences, economics, and social sciences. This book presents the key concepts, theory, and computer code written in R, helping readers with limited initial knowledge of random processes to become confident in their understanding and application of these principles in their own research. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Language: English
Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Add to basketPaperback. Condition: Brand New. 400 pages. 10.00x7.00x1.00 inches. In Stock.
Language: English
Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Add to basketPaperback / softback. Condition: New. New copy - Usually dispatched within 4 working days.
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Published by Oxford University Press, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Add to basketPaperback. Condition: Brand New. 400 pages. 10.00x7.00x1.00 inches. In Stock.
Language: English
Published by Oxford University Press, 2022
ISBN 10: 0198862520 ISBN 13: 9780198862529
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Kartoniert / Broschiert. Condition: New. Über den AutorMarco Bittelli received a degree in Agricultural Sciences from the University of Bologna, Italy, in 1994 and an M.S. and a Ph.D. in Soil Physics from Washington State University, USA, in 2001. He teaches Soil and Envir.
Language: English
Published by Oxford University Press Jan 2023, 2023
ISBN 10: 0198862520 ISBN 13: 9780198862529
Seller: AHA-BUCH GmbH, Einbeck, Germany
Taschenbuch. Condition: Neu. Neuware - Random process analysis (RPA) is used as a mathematical model in physics, chemistry, biology, computer science, information theory, economics, environmental science, and many other disciplines. Over time, it has become more and more important for the provision of computer code and data sets. This book presents the key concepts, theory, and computer code written in R, helping readers with limited initial knowledge of random processes to become confident in their understanding and application of these principles in their own research. Consistent with modern trends in university education, the authors make readers active learners with hands-on computer experiments in R code directing them through RPA methods and helping them understand the underlying logic. Each subject is illustrated with real data collected in experiments performed by the authors or taken from key literature. As a result, the reader can promptly apply the analysis to their own data, making this book an invaluable resource for undergraduate and graduate students, as well as professionals, in physics, engineering, biophysical and environmental sciences, economics, and social sciences.