All of Statistics: A Concise Course in Statistical Inference

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All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)

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 nonparametric curve estimation, bootstrapping, and clasÂ sification, 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 analyzing data. For some time, statistics research was conÂ ducted in statistics departments while data mining and machine learning reÂ search was conducted in computer science departments. Statisticians thought that computer scientists were reinventing the wheel. Computer scientists thought that statistical theory didn't apply to their problems. Things are changing. Statisticians now recognize that computer scientists are making novel contributions while computer scientists now recognize the generality of statistical theory and methodology. Clever data mining algoÂ rithms are more scalable than statisticians ever thought possible. Formal staÂ tistical theory is more pervasive than computer scientists had realized.

Country	USA
Author	Larry Wasserman
Binding	Kindle Edition
EISBN	9780387217369
Format	Kindle eBook
Label	Springer
Manufacturer	Springer
NumberOfPages	442
PublicationDate	2013-12-11
Publisher	Springer
ReleaseDate	2013-12-11
Studio	Springer

All of Statistics: A Concise Course in Statistical Inference (Springer Texts in Statistics)

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