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Using Multivariate Statistics (4th Edition)

Using Multivariate Statistics (4th Edition)

Using Multivariate Statistics (4th Edition)
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Using Multivariate Statistics (4th Edition) Hardback - 2000 - 4th Edition

by Barbara G. Tabachnick

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Details

  • Title Using Multivariate Statistics (4th Edition)
  • Author Barbara G. Tabachnick
  • Binding Hardback
  • Edition number 4th
  • Edition 4
  • Condition Used - Good
  • Pages 966
  • Volumes 1
  • Language ENG
  • Publisher Allyn & Bacon, Old Tappan, New Jersey, U.S.A.
  • Publication date 2000-08
  • Illustrated Yes
  • Bookseller's Inventory # ANAIS-0321056779
  • ISBN 9780321056771 / 0321056779
  • Weight 3.6 lbs (1.63 kg)
  • Dimensions 9.5 x 7.8 x 1.7 in (24.13 x 19.81 x 4.32 cm)
  • Size 7.6x1.9x9.3
  • Category Mathematics
  • Library of Congress subjects Multivariate analysis
  • Library of Congress Catalogue Number 00025300
  • Dewey Decimal Code 519.535
  • Quantity available 1

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From the publisher

This text takes a practical approach to multivariate data analysis, with an introductionto the most commonly encountered statistical and multivariate techniques. Using Multivariate Statistics provides practical guidelines for conducting numerous types of multivariate statistical analyses. It gives syntax and output for accomplishing many analyses through the most recent releases of SAS, SPSS, and SYSTAT, some not available in software manuals. The book maintains its practical approach, still focusing on the benefits and limitations of applications of a technique to a data set - when, why, and how to do it. Overall, it provides advanced students with a timely and comprehensive introduction to today's most commonly encountered statistical and multivariate techniques, while assuming only a limited knowledge ofhigher-level mathematics. *A new chapter on survival analysis (Ch. 15) allows students to analyze data where the outcome is time until something happens. This is very popular in biomedical research. *A new chapter on time series analysis (Ch. 16) encourages students to learn to model patterns in data gathered over many trials and to test for the effectiveness on an intervention (

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