- Paperback: 513 pages
- Publisher: Peer Management Consultants, Ltd. (September 1992)
- Language: English
- ISBN-10: 0963502700
- ISBN-13: 978-0963502704
- Product Dimensions: 9.8 x 6.7 x 1.1 inches
- Shipping Weight: 2 pounds (View shipping rates and policies)
- Average Customer Review: 4.7 out of 5 stars See all reviews (4 customer reviews)
- Amazon Best Sellers Rank: #3,593,030 in Books (See Top 100 in Books)
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Data Analysis for Scientists and Engineers
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Top Customer Reviews
The author does a fine job of explaining the nature of data collection and scientific investigation, and also proves rigorously the properties of the most common probability distributions, such as the binomial, hypergeometric, Poisson, Gaussian, Student's t, negative binomial, multinomial, exponential, Weibull, and log-normal distributions. Noticeably missing is the Pareto distribution, which has become very important in network modeling and computational biology. Also included is a brief introduction to Monte Carlo experiments. There has been an explosion in the last decade in the use of Monte Carlo simulations, particularly in financial engineering, and this will no doubt continue in years to come.
Statistical inference is also treated very adequately in this book, and should prepare the beginning reader for using the statistical packages currently available. Missing of course are discussions of time series and nonlinear regression using neural networks, but reader who need exposure to these areas will be prepared after reading this book.
Computational and artificial intelligence are quickly overtaking the world of statistical estimation and modeling, and future books in data analysis will no doubt be considerably different than this one. But programming and designing these intelligent programs or machines will still require a thorough understanding of statistical concepts, and this book still serves well in that goal.
The book is a bit old. The sections on Monte Carlo methods and curve fitting are ok, but were written before computers were as common as they are now. Especially for curve fitting Bevington will be a more useful book.