- Hardcover: 792 pages
- Publisher: Oxford University Press; 1 edition (January 21, 2011)
- Language: English
- ISBN-10: 0195089650
- ISBN-13: 978-0195089653
- Product Dimensions: 9.4 x 1.7 x 6.4 inches
- Shipping Weight: 2.9 pounds (View shipping rates and policies)
- Average Customer Review: 4 customer reviews
- Amazon Best Sellers Rank: #1,696,235 in Books (See Top 100 in Books)
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Exploring Data in Engineering, the Sciences, and Medicine 1st Edition
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About the Author
Ronald Pearson has held a wide variety of technical positions in both academia and industry, including the DuPont Company, the Swiss Federal Institute of Technology (ETH, Zurich), the Tampere University of Technology in Tampere, Finland, and most recently, the Travelers Companies. Dr. Pearson's experience has included the analysis and modeling of industrial process operating data, the design of nonlinear digital filters for data cleaning applications, the analysis of historical clinical data, and he is currently involved in developing models for predictive analytics applied to large business datasets. His research interests include model structure selection for nonlinear discrete-time dynamic models of empirical data, the algebraic characterization and design of nonlinear digital filters, and the development of exploratory data analysis techniques for large datasets involving mixed data types.
Top customer reviews
I found this book to be an efficient way to get a deeper understanding of statistics as it applies to practical data analysis. What I'm looking for now is a book teaches the relationships between the techniques of machine learning and traditional statistics.