All of Statistics: A Concise Course in Statistical Inference
Larry Wasserman
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Description for All of Statistics: A Concise Course in Statistical Inference
Paperback. Series: Springer Texts in Statistics. Num Pages: 462 pages, biography. BIC Classification: PBT. Category: (P) Professional & Vocational. Dimension: 234 x 156 x 23. Weight in Grams: 651.
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines.
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 ... Read more
Taken literally, the title "All of Statistics" is an exaggeration. But in spirit, the title is apt, as the book does cover a much broader range of topics than a typical introductory book on mathematical statistics. This book is for people who want to learn probability and statistics quickly. It is suitable for graduate or advanced undergraduate students in computer science, mathematics, statistics, and related disciplines.
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 ... Read more
Product Details
Format
Paperback
Publication date
2010
Publisher
Springer-Verlag New York Inc.
Condition
New
Series
Springer Texts in Statistics
Number of Pages
442
Place of Publication
New York, NY, United States
ISBN
9781441923226
SKU
V9781441923226
Shipping Time
Usually ships in 15 to 20 working days
Ref
99-15
About Larry Wasserman
Larry Wasserman is Professor of Statistics at Carnegie Mellon University. He is also a member of the Center for Automated Learning and Discovery in the School of Computer Science. His research areas include nonparametric inference, asymptotic theory, causality, and applications to astrophysics, bioinformatics, and genetics. He is the 1999 winner of the Committee of Presidents of Statistical Societies Presidents' Award ... Read more
Reviews for All of Statistics: A Concise Course in Statistical Inference
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 ... Read more