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An Introduction to the Bootstrap
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Format: Hardback
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Book Hero Magic created this recommendation. While it's new and still learning, it may not be perfect - your feedback is welcome! IS THIS YOUR NEXT READ?
Ideal for scientists, engineers, statisticians, and students wanting a practical, clear guide to bootstrap techniques without heavy mathematical barriers.
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See moreAn exploration of the many different bootstrap techniques. It discusses useful statistical techniques through real data examples and covers nonparametric regression, density estimation, classification trees, and least median squares regression. There are numerous exercises.
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Book Hero Magic formatted this description to make it easier to read. While it's new and
still learning, it may not be perfect - your
feedback is welcome!
Description
Statistics is a subject of many uses and surprisingly few effective practitioners. The traditional road to statistical knowledge is blocked, for most, by a formidable wall of mathematics. The approach in An Introduction to the Bootstrap avoids that wall.
It arms scientists and engineers, as well as statisticians, with the computational techniques they need to analyse and understand complicated data sets.
Book Hero Magic summarised reviews for this book. While it's new and still learning, it may not be perfect - your feedback is welcome! HOW HAS THIS BEEN REVIEWED?
Praised for clarity and accessibility: Reviewers commend the authors for simplifying challenging statistical concepts, making the book ideal for both students and practitioners. It's highlighted as a valuable reference for engineers seeking to understand bootstrap methods.
Book Details
INFORMATION
ISBN: 9780412042317
Publisher: Taylor & Francis Ltd
Format: Hardback
Date Published: 15 May 1994
Country: United Kingdom
Imprint: Chapman & Hall/CRC
Audience: Tertiary education, Professional and scholarly
DIMENSIONS
Width: 152.0mm
Height: 229.0mm
Weight: 756g
Pages: 456
About the Author
Bradley Efron, Department of Statistics Stanford University and Robert J. Tibshirani, Department of Preventative Medicine and Biostatistics and Department of Statistics, University of Toronto.
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