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A timely update of the classic book on the theory and application of random data analysis
First published in 1971, Random Data served as an authoritative book on the analysis of experimental physical data for engineering and scientific applications. This Fourth Edition features coverage of new developments in random data management and analysis procedures that are applicable to a broad range of applied fields, from the aerospace and automotive industries to oceanographic and biomedical research.
This new edition continues to maintain a balance of classic theory and novel techniques. The authors expand on the treatment of random data analysis theory, including derivations of key relationships in probability and random process theory. The book remains unique in its practical treatment of nonstationary data analysis and nonlinear system analysis, presenting the latest techniques on modern data acquisition, storage, conversion, and qualification of random data prior to its digital analysis. The Fourth Edition also includes:
- A new chapter on frequency domain techniques to model and identify nonlinear systems from measured input/output random data
- New material on the analysis of multiple-input/single-output linear models
- The latest recommended methods for data acquisition and processing of random data
- Important mathematical formulas to design experiments and evaluate results of random data analysis and measurement procedures
- Answers to the problem in each chapter
Comprehensive and self-contained, Random Data, Fourth Edition is an indispensible book for courses on random data analysis theory and applications at the upper-undergraduate and graduate level. It is also an insightful reference for engineers and scientists who use statistical methods to investigate and solve problems with dynamic data.
- Sales Rank: #512443 in Books
- Published on: 2010-02-08
- Original language: English
- Number of items: 1
- Dimensions: 9.60" h x 1.50" w x 6.50" l, 2.24 pounds
- Binding: Hardcover
- 640 pages
Review
"...time series analysts will certainly wish to have continuing access to both books and libraries will want to get copies of both new editions." (Technometrics, Vol. 42, No. 4, May 2001)
The book is a good practical reference for working engineers and scientists in many fields. (Zentralblatt Math, Volume 953, March 2001)
"...can be recommended for practical working engineers and scientists to support their daily work, as well as for university readers as a teaching textbook in advanced courses" (Measurement Science & Technology, December 2000)
From the Publisher
A revised and expanded edition of this classic reference/text, covering the latest techniques for the analysis and measurement of stationary and nonstationary random data passing through physical systems. With more than 100,000 copies in print and six foreign translations, the first edition standardized the methodology in this field. This new edition covers all new procedures developed since 1971 and extends the application of random data analysis to aerospace and automotive research; digital data analysis; dynamic test programs; fluid turbulence analysis; industrial noise control; oceanographic data analysis; system identification problems; and many other fields. Includes new formulas for statistical error analysis of desired estimates, new examples and problem sets.
From the Back Cover
A timely update of the classic book on the theory and application of random data analysis
First published in 1971, Random Data served as an authoritative book on the analysis of experimental physical data for engineering and scientific applications. This Fourth Edition features coverage of new developments in random data management and analysis procedures that are applicable to a broad range of applied fields, from the aerospace and automotive industries to oceanographic and biomedical research.
This new edition continues to maintain a balance of classic theory and novel techniques. The authors expand on the treatment of random data analysis theory, including derivations of key relationships in probability and random process theory. The book remains unique in its practical treatment of nonstationary data analysis and nonlinear system analysis, presenting the latest techniques on modern data acquisition, storage, conversion, and qualification of random data prior to its digital analysis. The Fourth Edition also includes:
-
A new chapter on frequency domain techniques to model and identify nonlinear systems from measured input/output random data
-
New material on the analysis of multiple-input/single-output linear models
-
The latest recommended methods for data acquisition and processing of random data
-
Important mathematical formulas to design experiments and evaluate results of random data analysis and measurement procedures
-
Answers to the problem in each chapter
Comprehensive and self-contained, Random Data, Fourth Edition is an indispensible book for courses on random data analysis theory and applications at the upper-undergraduate and graduate level. It is also an insightful reference for engineers and scientists who use statistical methods to investigate and solve problems with dynamic data.
Most helpful customer reviews
38 of 39 people found the following review helpful.
Random data and Coherent content
By J. K. Hong
My major is meteorology and deal with time series data, which have huge amount of data number. This book is very helpful to me. I have to determine the statistical significance of my data and check up the assumptions both in time and frequency domain, before deciding the statistical tests. I read a few this kinds of books but they were only concentrated on the explanation of simple statistics theory and then came to stop after showing only a few simple examples. So it is difficult to apply to my raw data because the assumptions that were applied to the theory were invalid in real situation. For example, ¡°Introduction to probability and statistics for engineers and scientist, by Sheldon M. Ross¡± is too theoretical to me and the application of theories is biased to the persons who are interested in small data set. Additionally, many books assumed the normal distribution and did not refer how we could test these assumptions. In analyzing the time series, not only is important the data analysis in time domain, but also the analysis in frequency domain. ¡°Applied Statistical time series analysis by Shumway¡± dealt with it. However, ¡°Random data by Bendat and Piersol¡± more will be helpful to the people who deal with time series, want to design statistical filters and to do the statistical tests and need more profound and systematic theories and understanding.
0 of 0 people found the following review helpful.
Great contents Some bracket(
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