Overview
- Focuses on analytical skills as well as applying formulae
- Provides motivations and intuition so that readers can apply concepts
- Second Edition implements challenges of contemporary data science
Part of the book series: Springer Texts in Statistics (STS)
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Table of contents (16 chapters)
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Front Matter
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Back Matter
Keywords
About this book
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 ten chapters contains at least one section of case study. The last six chapters are devoted to special areas of applications. This new edition introduces a final chapter dedicated to random matrix theory, as well as expanded treatment of inequalities and mixed effects models.
The book's case studies and applications-oriented chapters demonstrate how to use methods developed from large sample theory in real world situations. The book is supplemented by a large number of exercises, giving readers opportunity to practice what they have learned. Appendices provide context for matrix algebra and mathematical statistics. The Second Edition seeks to address new challenges in data science.
This text is intended for a wide audience, ranging from senior undergraduate students to researchers with doctorates. A first course in mathematical statistics and a course in calculus are prerequisites..
Authors and Affiliations
About the author
Bibliographic Information
Book Title: Large Sample Techniques for Statistics
Authors: Jiming Jiang
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/978-3-030-91695-4
Publisher: Springer Cham
eBook Packages: Mathematics and Statistics, Mathematics and Statistics (R0)
Copyright Information: The Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerland AG 2022
Hardcover ISBN: 978-3-030-91694-7Published: 05 April 2022
Softcover ISBN: 978-3-030-91697-8Published: 06 April 2023
eBook ISBN: 978-3-030-91695-4Published: 04 April 2022
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 2
Number of Pages: XV, 685
Number of Illustrations: 7 b/w illustrations, 2 illustrations in colour
Topics: Probability Theory and Stochastic Processes, Statistical Theory and Methods