Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Añadir al carritoCondición: New. Num Pages: 408 pages, 96 line illus. 7 tables. BIC Classification: GPH; PD; TBC. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 212 x 262 x 30. Weight in Grams: 1186. . 2016. Illustrated. hardcover. . . . .
Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
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Idioma: Inglés
Publicado por Princeton University Press, US, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
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Añadir al carritoHardback. Condición: New. Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix.Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. * In-depth discussion of data analysis for scientists and engineers * Coverage of both frequentist and Bayesian approaches to data analysis * Extensive look at analysis techniques for time-series data and images * Detailed exploration of linear and nonlinear modeling of data * Emphasis on error analysis * Instructor's manual (available only to professors).
Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: Majestic Books, Hounslow, Reino Unido
EUR 105,80
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Añadir al carritoCondición: New. pp. 416.
Idioma: Inglés
Publicado por Princeton University Press, US, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 114,14
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Añadir al carritoHardback. Condición: New. Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix.Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. * In-depth discussion of data analysis for scientists and engineers * Coverage of both frequentist and Bayesian approaches to data analysis * Extensive look at analysis techniques for time-series data and images * Detailed exploration of linear and nonlinear modeling of data * Emphasis on error analysis * Instructor's manual (available only to professors).
Idioma: Inglés
Publicado por Princeton University Press, New Jersey, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 115,09
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Añadir al carritoHardcover. Condición: new. Hardcover. Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix.Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. * In-depth discussion of data analysis for scientists and engineers * Coverage of both frequentist and Bayesian approaches to data analysis * Extensive look at analysis techniques for time-series data and images * Detailed exploration of linear and nonlinear modeling of data * Emphasis on error analysis * Instructor's manual (available only to professors) Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques w Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: Kennys Bookstore, Olney, MD, Estados Unidos de America
EUR 106,61
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Añadir al carritoCondición: New. Num Pages: 408 pages, 96 line illus. 7 tables. BIC Classification: GPH; PD; TBC. Category: (P) Professional & Vocational; (U) Tertiary Education (US: College). Dimension: 212 x 262 x 30. Weight in Grams: 1186. . 2016. Illustrated. hardcover. . . . . Books ship from the US and Ireland.
Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: THE SAINT BOOKSTORE, Southport, Reino Unido
EUR 95,92
Cantidad disponible: 10 disponibles
Añadir al carritoHardback. Condición: New. New copy - Usually dispatched within 4 working days.
Idioma: Inglés
Publicado por Princeton University Press, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 127,40
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Añadir al carritoCondición: New. pp. 416.
EUR 111,74
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Añadir al carritoHardcover. Condición: Brand New. 393 pages. 10.00x8.25x1.00 inches. In Stock.
Idioma: Inglés
Publicado por Princeton University Press, US, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
EUR 112,37
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Añadir al carritoHardback. Condición: New. Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix.Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. * In-depth discussion of data analysis for scientists and engineers * Coverage of both frequentist and Bayesian approaches to data analysis * Extensive look at analysis techniques for time-series data and images * Detailed exploration of linear and nonlinear modeling of data * Emphasis on error analysis * Instructor's manual (available only to professors).
Idioma: Inglés
Publicado por Princeton University Press, US, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: Rarewaves.com UK, London, Reino Unido
EUR 107,25
Cantidad disponible: 5 disponibles
Añadir al carritoHardback. Condición: New. Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix.Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. * In-depth discussion of data analysis for scientists and engineers * Coverage of both frequentist and Bayesian approaches to data analysis * Extensive look at analysis techniques for time-series data and images * Detailed exploration of linear and nonlinear modeling of data * Emphasis on error analysis * Instructor's manual (available only to professors).
Idioma: Inglés
Publicado por Princeton University Press, New Jersey, 2016
ISBN 10: 0691169926 ISBN 13: 9780691169927
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 171,27
Cantidad disponible: 1 disponibles
Añadir al carritoHardcover. Condición: new. Hardcover. Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques when necessary. Robinson divides the book into three sections. The first section covers basic concepts in probability and includes a chapter on Monte Carlo methods with an extended discussion of Markov chain Monte Carlo sampling. The second section introduces statistics and then develops tools for fitting models to data, comparing and contrasting techniques from both frequentist and Bayesian perspectives. The final section is devoted to methods for analyzing sequences of data, such as correlation functions, periodograms, and image reconstruction. While it goes beyond elementary statistics, the text is self-contained and accessible to readers from a wide variety of backgrounds. Specialized mathematical topics are included in an appendix.Based on a graduate course on data analysis that the author has taught for many years, and couched in the looser, workaday language of scientists and engineers who wrestle directly with data, this book is ideal for courses on data analysis and a valuable resource for students, instructors, and practitioners in the physical sciences and engineering. * In-depth discussion of data analysis for scientists and engineers * Coverage of both frequentist and Bayesian approaches to data analysis * Extensive look at analysis techniques for time-series data and images * Detailed exploration of linear and nonlinear modeling of data * Emphasis on error analysis * Instructor's manual (available only to professors) Data Analysis for Scientists and Engineers is a modern, graduate-level text on data analysis techniques for physical science and engineering students as well as working scientists and engineers. Edward Robinson emphasizes the principles behind various techniques so that practitioners can adapt them to their own problems, or develop new techniques w Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.