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PASW Statistics 18 Statistical Procedures Companion

Book Cover PASW Statistics 18 Statistical Procedures Companion
by Marija J. Norušis
ISBN-10: 0-321-67336-0
ISBN-13: 978-0-321-67336-7
pages 648

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You have all of the essential components: software with enough options to make a whirling dervish take pause; a data set of questionable virtue cast in a starring role; and a plot waiting to unfold. Directing this production to a satisfying conclusion isn't easy. The goal of the PASW Statistics 18 Statistical Procedures Companion is to point you in the right direction.

Contents at a glance:

Preparing data for analysis:
Introduction to SPSS/PASW; the data file; defining the data; creating new variables; transforming existing variables; checking data definitions; cleaning data

Describing data:
Tables; graphs; OLAP cubes; measures of central tendency and dispersion; standard scores; the normal distribution; measures of association

Testing simple hypotheses:
Basics of hypothesis testing; t-tests; oneway analysis of variance; multiple comparisons; nonparametric tests; chi square tests; correlation; partial correlation

Building models:
Bivariate and multiple linear regression; loglinear models; discriminant analysis; binary logistic regression; factor analysis; cluster analysis

Using the General Linear Model:
Univariate models; multivariate models; repeated measures

Analyzing scales:
Reliability analysis


  • Chapters start with concise overviews and examples of the use of the procedure
  • Tips and warnings help you to avoid common mistakes and work efficiently
  • Practical discussions explain the statistical background for each procedure
  • Instructions make it easy to obtain the output in the book
  • Examples are from diverse disciplines, including psychology, sociology, education, archaeology, medicine, library science, nursing and journalism
  • Reviewed by SPSS/PASW Inc. staff

Examples include:

  • Is a truancy reduction program effective?
  • What variables are associated with newspaper readership?
  • Can you predict percent body fat from easily obtainable measurements?
  • What factors are associated with "getting ahead"?
  • How can you predict Internet use from demographic characteristics?

New to this edition:

Updated for Release 18 of the SPSS/PASW Software.

© 2005-2011 Marija Norušis: IBM SPSS Statistics Guides Site designed by Kenny Kim Photography