Authors:
- Provides a concise introduction to a larger number of topics than are usually included in a graduate-level mathematical statistics class
Part of the book series: Springer Texts in Statistics (STS)
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Table of contents (24 chapters)
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Front Matter
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Probability
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Front Matter
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Statistical Models and Methods
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Front Matter
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About this book
The book includes modern topics like non-parametric curve estimation, bootstrapping, and classification, topics that are usually relegated to follow-up courses. The reader is presumed to know calculus and a little linear algebra. No previous knowledge of probability and statistics is required. Statistics, data mining, and machine learning are all concerned with collecting and analysing data.
Reviews
Winner of the 2005 DeGroot Prize.
From the reviews:
"Presuming no previous background in statistics and described by the author as "demanding" yet "understandable because the material is as intuitive as possible" (p. viii), this certainly would be my choice of textbook if I was required to learn mathematical statistics again for a couple of semesters." Technometrics, August 2004
"This book should be seriously considered as a text for a theoretical statsitics course for non-majors, and perhaps even for majors...The coverage of emerging and important topics is timely and welcomed...you should have this book on your desk as a reference to nothing less than 'All of Statistics.'" Biometrics, December 2004
"Although All of Statistics is an ambitious title, this book is a concise guide, as the subtitle suggests....I recommend it to anyone who has an interest in learning something new about statistical inference. There is something here for everyone." The American Statistician, May 2005
"As the title of the book suggests, ‘All of Statistics’ covers a wide range of statistical topics. … The number of topics covered in this book is vast … . The greatest strength of this book is as a first point of reference for a wide range of statistical methods. … I would recommend this book as a useful and interesting introduction to a large number of statistical topics for non-statisticians and also as a useful reference book for practicing statisticians." (Matthew J. Langdon, Journal of Applied Statistics, Vol. 32 (1), January, 2005)
"This book was written specifically to give students a quick but sound understanding of modern statistics, and its coverage is very wide. … The book is extremely well done … ." (N. R. Draper, Short Book Reviews, Vol. 24 (2), 2004)
"This is most definitely a book about mathematical statistics. It is full of theorems and proofs … . Presuming no previous background in statistics … this certainly would be my choice of textbook if I was required to learn mathematical statistics again for a couple of semesters." (Eric R. Ziegel, Technometrics, Vol. 46 (3), August, 2004)
"The author points out that this book is for those who wish to learn probability and statistics quickly … . this book will serve as a guideline for instructors as to what should constitute a basic education in modern statistics. It introduces many modern topics … . Adequate references are provided at the end of each chapter which the instructor will be able to use profitably … ." (Arup Bose, Sankhya, Vol. 66 (3), 2004)
"The amount of material that is covered in this book is impressive. … the explanations are generally clear and the wide range of techniques that are discussed makes it possible to include a diverse set of examples … . The worked examples are complemented with numerous theoretical and practical exercises … . is a very useful overview of many areas of modern statistics and as such will be very useful to readers who require such a survey. Library copies would also see plenty of use." (Stuart Barber, Journal of the Royal Statistical Society, Series A – Statistics in Society, Vol. 168 (1), 2005)
Authors and Affiliations
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Department of Statistics, Carnegie Mellon University, Pittsburgh, USA
Larry Wasserman
About the author
Bibliographic Information
Book Title: All of Statistics
Book Subtitle: A Concise Course in Statistical Inference
Authors: Larry Wasserman
Series Title: Springer Texts in Statistics
DOI: https://doi.org/10.1007/978-0-387-21736-9
Publisher: Springer New York, NY
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eBook Packages: Springer Book Archive
Copyright Information: Springer Science+Business Media, LLC, part of Springer Nature 2004
Hardcover ISBN: 978-0-387-40272-7Published: 04 December 2003
Softcover ISBN: 978-1-4419-2322-6Published: 01 December 2010
eBook ISBN: 978-0-387-21736-9Published: 11 December 2013
Series ISSN: 1431-875X
Series E-ISSN: 2197-4136
Edition Number: 1
Number of Pages: XX, 442
Topics: Computational Mathematics and Numerical Analysis, Probability Theory and Stochastic Processes, Complex Systems, Statistical Theory and Methods, Probability and Statistics in Computer Science, Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences