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Vidakovic, Brani

Engineering Biostatistics

Vidakovic, Brani - Engineering Biostatistics, ebook

97,00€

Ebook, ePUB with Adobe DRM
ISBN: 9781119168980
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Printing221 pages with an additional page accrued every 4 hours, capped at 221 pages
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Provides a one-stop resource for engineers learning biostatistics using MATLAB® and WinBUGS

Through its scope and depth of coverage, this book addresses the needs of the vibrant and rapidly growing bio-oriented engineering fields while implementing software packages that are familiar to engineers. The book is heavily oriented to computation and hands-on approaches so readers understand each step of the programming. Another dimension of this book is in parallel coverage of both Bayesian and frequentist approaches to statistical inference. It avoids taking sides on the classical vs. Bayesian paradigms, and many examples in this book are solved using both methods. The results are then compared and commented upon. Readers have the choice of MATLAB® for classical data analysis and WinBUGS/OpenBUGS for Bayesian data analysis. Every chapter starts with a box highlighting what is covered in that chapter and ends with exercises, a list of software scripts, datasets, and references.

Engineering Biostatistics: An Introduction using MATLAB® and WinBUGS also includes:

  • parallel coverage of classical and Bayesian approaches, where appropriate
  • substantial coverage of Bayesian approaches to statistical inference
  • material that has been classroom-tested in an introductory statistics course in bioengineering over several years
  • exercises at the end of each chapter and an accompanying website with full solutions and hints to some exercises, as well as additional materials and examples

Engineering Biostatistics: An Introduction using MATLAB® and WinBUGScan serve as a textbook for introductory-to-intermediate applied statistics courses, as well as a useful reference for engineers interested in biostatistical approaches.

Keywords: biostatistics, matlab, winbugs, bio-oriented engineering fields, bayesian and frequentist approaches, classical vs. bayesian paradigms, statistical inference, applied statistics

Author(s)
Publisher
John Wiley and Sons, Inc.
Publication year
2017
Language
en
Edition
1
Imprint
Wiley
Series
Wiley Series in Probability and Statistics
Page amount
992 pages
Category
Natural Sciences
Format
Ebook
eISBN (ePUB)
9781119168980
Printed ISBN
9781119168966

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