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Science/Engineering Large Sample Techniques for Statistics

Posted on 2010-07-02




Name:Science/Engineering Large Sample Techniques for Statistics
ASIN/ISBN:1441968261
File size:3.3 Mb
Publish Date: 2010
ISBN: 1441968261
Pages: 609 pages
File Type: PDF
File Size: 3,3 MB
Other Info: Springer
   Science/Engineering Large Sample Techniques for Statistics

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Jiming Jiang, "Large Sample Techniques for Statistics"

This book offers a comprehensive guide to large sample techniques in statistics. More importantly, it focuses on thinking skills rather than just what formulae to use; it provides motivations, and intuition, rather than detailed proofs; it begins with very simple techniques, and connects theory and applications in entertaining ways. The first five chapters review some of the basic techniques, such as the fundamental epsilon-delta arguments, Taylor expansion, different types of convergence, and inequalities.

The next five chapters discuss limit theorems in specific situations of observational data. Each of the first 10 chapters contains at least one section of case study. The last five chapters are devoted to special areas of applications. The sections of case studies and chapters of applications fully demonstrate how to use methods developed from large sample theory in various, less-than-textbook situations.

The book is supplemented by a large number of exercises, giving the readers plenty of opportunities to practice what they have learned. The book is mostly self-contained with the appendices providing some backgrounds for matrix algebra and mathematical statistics. The book is intended for a wide audience, ranging from senior undergraduate students to researchers with Ph.D. degrees. A first course in mathematical statistics and a course in calculus are prerequisites.

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