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IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference
Contributor(s): George, Darren (Author), Mallery, Paul (Author)

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ISBN: 1032070900     ISBN-13: 9781032070902
Publisher: Routledge
OUR PRICE: $294.00  

Binding Type: Hardcover - See All Available Formats & Editions
Published: December 2021
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Temporarily out of stock - Will ship within 2 to 5 weeks
Additional Information
BISAC Categories:
- Education | Statistics
- Education | Computers & Technology
- Psychology
Dewey: 005.55
LCCN: 2021030200
Physical Information: 418 pages
 
Descriptions, Reviews, Etc.
Publisher Description:

IBM SPSS Statistics 27 Step by Step: A Simple Guide and Reference, seventeenth edition, takes a straightforward, step-by-step approach that makes SPSS software clear to beginners and experienced researchers alike. Extensive use of four-color screen shots, clear writing, and step-by-step boxes guide readers through the program. Output for each procedure is explained and illustrated, and every output term is defined. Exercises at the end of each chapter support students by providing additional opportunities to practice using SPSS.

This book covers the basics of statistical analysis and addresses more advanced topics such as multidimensional scaling, factor analysis, discriminant analysis, measures of internal consistency, MANOVA (between- and within-subjects), cluster analysis, Log-linear models, logistic regression and a chapter describing residuals. Back matter includes a description of data files used in exercises, an exhaustive glossary, suggestions for further reading and a comprehensive index.

IBM SPSS Statistics 27 Step by Step is distributed in 85 countries, has been an academic best seller through most of the earlier editions, and has proved an invaluable aid to thousands of researchers and students.

New to this edition:

  • Screenshots, explanations, and step-by-step boxes have been fully updated to reflect SPSS 27
  • A new chapter on a priori power analysis helps researchers determine the sample size needed for their research before starting data collection.
 
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