Empirical Model Building: Data, Models, and Reality by James R. Thompson: New

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Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Empirical Model Building: Data, Models, and Reality
Publication Date
2011-12-02
Edition Number
2
ISBN
9780470467039
Subject Area
Mathematics, Science
Publication Name
Empirical Model Building : Data, Models, and Reality
Publisher
Wiley & Sons, Incorporated, John
Item Length
9.6 in
Subject
Probability & Statistics / General, General, Research & Methodology
Publication Year
2011
Series
Wiley Series in Probability and Statistics Ser.
Type
Textbook
Format
Hardcover
Language
English
Item Height
1.1 in
Author
James R. Thompson
Item Weight
27.7 Oz
Item Width
6.4 in
Number of Pages
464 Pages
Category

About this product

Product Identifiers

Publisher
Wiley & Sons, Incorporated, John
ISBN-10
0470467037
ISBN-13
9780470467039
eBay Product ID (ePID)
109131582

Product Key Features

Number of Pages
464 Pages
Publication Name
Empirical Model Building : Data, Models, and Reality
Language
English
Publication Year
2011
Subject
Probability & Statistics / General, General, Research & Methodology
Type
Textbook
Subject Area
Mathematics, Science
Author
James R. Thompson
Series
Wiley Series in Probability and Statistics Ser.
Format
Hardcover

Dimensions

Item Height
1.1 in
Item Weight
27.7 Oz
Item Length
9.6 in
Item Width
6.4 in

Additional Product Features

Edition Number
2
Intended Audience
Scholarly & Professional
LCCN
2011-013569
Dewey Edition
23
Reviews
"It is also an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work." ( Mathematical Reviews , 2012) "Empirical Model Building, Second Edition is an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work." (TMCnet.com, 18 January 2012)
Series Volume Number
794
Illustrated
Yes
Dewey Decimal
519.5/7
Table Of Content
Preface. 1.Models of Growth and Decay. 2. Models of Competition, Survival, and Combat. 3. Epidemics. 4. Bootstrapping. 5. Monte-Carlo Solution of Differential Equations. 6. SIMEST, SMIDAT, and Psuedoreality. 7. Exploratory Data Analysis. 8. Noise Killing Chaos. 9. Bayesian Approaches. 10. Multivariate and Robust Procedures in Statistical Process Control. 11. Optimization and Estimation in the Real (Noisy) World. 12. Utility and Group Preference. 13. A Primer in Sampling. 14. Stock Market: Strategies Based on Data versus Strategies Based on Ideology. Appendix A. A Brief Introduction to Probability and Statistics. Appendix B. Statistical Tables.
Synopsis
Praise for the First Edition "This...novel and highly stimulating book, which emphasizes solving real problems...should be widely read. It will have a positive and lasting effect on the teaching of modeling and statistics in general." - Short Book Reviews This new edition features developments and real-world examples that showcase essential empirical modeling techniques Successful empirical model building is founded on the relationship between data and approximate representations of the real systems that generated that data. As a result, it is essential for researchers who construct these models to possess the special skills and techniques for producing results that are insightful, reliable, and useful. Empirical Model Building: Data, Models, and Reality, Second Edition presents a hands-on approach to the basic principles of empirical model building through a shrewd mixture of differential equations, computer-intensive methods, and data. The book outlines both classical and new approaches and incorporates numerous real-world statistical problems that illustrate modeling approaches that are applicable to a broad range of audiences, including applied statisticians and practicing engineers and scientists. The book continues to review models of growth and decay, systems where competition and interaction add to the complextiy of the model while discussing both classical and non-classical data analysis methods. This Second Edition now features further coverage of momentum based investing practices and resampling techniques, showcasing their importance and expediency in the real world. The author provides applications of empirical modeling, such as computer modeling of the AIDS epidemic to explain why North America has most of the AIDS cases in the First World and data-based strategies that allow individual investors to build their own investment portfolios. Throughout the book, computer-based analysis is emphasized and newly added and updated exercises allow readers to test their comprehension of the presented material. Empirical Model Building, Second Edition is a suitable book for modeling courses at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work., Praise for the First Edition "This . . . novel and highly stimulating book, which emphasizes solving real problems . . . should be widely read. It will have a positive and lasting effect on the teaching of modeling and statistics in general." Short Book Reviews This new edition features developments and real-world examples that showcase essential empirical modeling techniques Successful empirical model building is founded on the relationship between data and approximate representations of the real systems that generated that data. As a result, it is essential for researchers who construct these models to possess the special skills and techniques for producing results that are insightful, reliable, and useful. Empirical Model Building: Data, Models, and Reality, Second Edition presents a hands-on approach to the basic principles of empirical model building through a shrewd mixture of differential equations, computer-intensive methods, and data. The book outlines both classical and new approaches and incorporates numerous real-world statistical problems that illustrate modeling approaches that are applicable to a broad range of audiences, including applied statisticians and practicing engineers and scientists. This new edition features developments and real-world examples that showcase essential empirical modeling techniques useful in various applications such as exploratory data analysis, diplomacy, combat, quality control, sampling, epidemiology, oncology, simulation-based solutions of differential equations, empirical investment strategies data-based modeling, and analysis of data sets of high dimensionality. The book continues to review models of growth and decay, systems where competition and interaction add to the complexity of the model while discussing both classical and non-classical data analysis methods. It now features further coverage of momentum-based investing practices and resampling techniques, showcasing their importance and expediency in the real world. The author provides applications of empirical modeling, such as computer modeling of the AIDS epidemic to explain why North America has most of the AIDS cases in the First World and data-based strategies that allow individual investors to build their own investment portfolios. Throughout the book, computer-based analysis is emphasized, and newly added and updated exercises allow readers to test their comprehension of the presented material. Empirical Model Building, Second Edition is a suitable book for modeling courses at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work., Praise for the First Edition This...novel and highly stimulating book, which emphasizes solving real problems...should be widely read. It will have a positive and lasting effect on the teaching of modeling and statistics in general. - Short Book Reviews This new edition features developments and real-world examples that showcase essential empirical modeling techniques Successful empirical model building is founded on the relationship between data and approximate representations of the real systems that generated that data. As a result, it is essential for researchers who construct these models to possess the special skills and techniques for producing results that are insightful, reliable, and useful. Empirical Model Building: Data, Models, and Reality, Second Edition presents a hands-on approach to the basic principles of empirical model building through a shrewd mixture of differential equations, computer-intensive methods, and data. The book outlines both classical and new approaches and incorporates numerous real-world statistical problems that illustrate modeling approaches that are applicable to a broad range of audiences, including applied statisticians and practicing engineers and scientists. The book continues to review models of growth and decay, systems where competition and interaction add to the complextiy of the model while discussing both classical and non-classical data analysis methods. This Second Edition now features further coverage of momentum based investing practices and resampling techniques, showcasing their importance and expediency in the real world. The author provides applications of empirical modeling, such as computer modeling of the AIDS epidemic to explain why North America has most of the AIDS cases in the First World and data-based strategies that allow individual investors to build their own investment portfolios. Throughout the book, computer-based analysis is emphasized and newly added and updated exercises allow readers to test their comprehension of the presented material. Empirical Model Building, Second Edition is a suitable book for modeling courses at the upper-undergraduate and graduate levels. It is also an excellent reference for applied statisticians and researchers who carry out quantitative modeling in their everyday work., First Edition users testify that the book is well written and expertly documented. The reader is introduced to provocative pointers such as the relevance of graphs, the meaning of interpretation, Henry Ford s Code of Practice, and Deming s 14 points, among others.
LC Classification Number
QA401

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