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| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
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| fixed length control field |
230831b xxu||||| |||| 00| 0 eng d |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
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| International Standard Book Number |
9783030916978 |
| 082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER |
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| Classification number |
519.52 |
| Item number |
JIA |
| 100 ## - MAIN ENTRY--PERSONAL NAME |
|---|
| Personal name |
Jiang, Jiming |
| 245 ## - TITLE STATEMENT |
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| Title |
Large sample techniques for statistics |
| 250 ## - EDITION STATEMENT |
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| Edition statement |
2nd ed. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT) |
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| Name of publisher, distributor, etc |
Springer, |
| Date of publication, distribution, etc |
2022 |
| Place of publication, distribution, etc |
Cham : |
| 300 ## - PHYSICAL DESCRIPTION |
|---|
| Extent |
xv, 685 p. ; |
| Dimensions |
24 cm. |
| Other physical details |
ill., |
| 365 ## - TRADE PRICE |
|---|
| Price amount |
69.99 |
| Price type code |
EUR |
| Unit of pricing |
94.90 |
| 490 ## - SERIES STATEMENT |
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| Series statement |
Springer texts in statistics |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE |
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| Bibliography, etc |
Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. |
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| Summary, etc |
This book offers a comprehensive guide to large sample techniques in statistics. With a focus on developing analytical skills and understanding motivation, Large Sample Techniques for Statistics begins with fundamental techniques, and connects theory and applications in engaging 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 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. |
| 650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM |
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| Topical term or geographic name as entry element |
Fundamental epsilon-delta arguments |
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| Topical term or geographic name as entry element |
Taylor expansion |
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| Topical term or geographic name as entry element |
Convergence |
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| Topical term or geographic name as entry element |
Inequalities |
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| Topical term or geographic name as entry element |
Observational data |
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| Topical term or geographic name as entry element |
Random matrix theory |
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| Topical term or geographic name as entry element |
Mixed effect models |
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| Topical term or geographic name as entry element |
Sample theory |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) |
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| Source of classification or shelving scheme |
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| Item type |
Books |