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Multivariate statistical methods : a primer / Bryan F.J. Manly, Jorge A. Navarro Alberto

By: Contributor(s): Material type: TextTextPublisher: Boca Raton, FL : CRC Press, Taylor & Francis Group, 2017Edition: Fourth editionDescription: xv, 253 pages : illustrations ; 23 cmContent type:
  • text
Media type:
  • unmediated
Carrier type:
  • volume
ISBN:
  • 9781498728966
Subject(s): LOC classification:
  • QA 278 .M315 2017
Summary: Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.
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Holdings
Item type Current library Call number Status Date due Barcode
Graduate Studies Graduate Studies DLSU-D GRADUATE STUDIES Graduate Studies QA 278 .M315 2017 (Browse shelf(Opens below)) Available 3CIR201766128

Includes bibliographical references and index

Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used.

The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.

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