9780205255887

IBM SPSS Statistics 19 Step by Step A Simple Guide and Reference

by ;
  • ISBN13:

    9780205255887

  • ISBN10:

    0205255884

  • Edition: 12th
  • Format: Paperback
  • Copyright: 9/14/2011
  • Publisher: Pearson
  • View Upgraded Edition

Note: Supplemental materials are not guaranteed with Rental or Used book purchases.

Purchase Benefits

  • Get Rewarded for Ordering Your Textbooks! Enroll Now

Supplemental Materials

What is included with this book?

  • The Used copy of this book is not guaranteed to include any supplemental materials. Typically, only the book itself is included. This is true even if the title states it includes any access cards, study guides, lab manuals, CDs, etc.

Summary

IBM SPSS Statistics 19 Step by Step: A Simple Guide and Referenceis a comprehensive guide to using SPSS that takes students step-by-step through all SPSS procedures.   Makes data analysis and SPSS procedures clear and accessible by presenting straightforward step-by-step instructions in each analysis chapter to clarify procedures. Hundreds of screen shots and step-by-step boxes guide the student through the program. All of the datasets used in the book are available for download online atwww.pearsonhighered.com/IRC.  Exercises at the end of each chapter give students an opportunity to practice using SPSS. Updated to reflect SPSS Version 19.0. 

Author Biography

Darren George is currently a professor at Canadian University College where he teaches personality psychology, social psychology, and research methods. He completed his M.A. in Experimental Psychology at California State University, Fullerton (1982); taught high school mathematics for nine years (1980-1989) at Mark Keppel High School (Alhambra, CA) and Mountain View High School (El Monte, CA); then completed a Psychology Ph.D. at UCLA with emphases in personality psychology, social psychology, and measurement & psychometrics.

 

Paul Mallery is currently a professor at La Sierra University where he teaches social psychology and experimental methodology (including the application of SPSS). He received his Ph.D. in Social Psychology from UCLA (1994) with emphases in statistics and political psychology. Paul formerly worked as a computer specialist, both programming and teaching computer usage.

Table of Contents

1. An overview of IBM SPSS Statistics 19 Step by Step

2. IBM SPSS Statistics Processes for PC and Mac: Mouse and keyboard processing, frequently-used dialog boxes, editing output, printing results, the Options Option

3. Creating and Editing a Data File

4. Managing Data: Listing cases, replacing missing values, computing new variables, recoding variables, exploring data, selecting cases, sorting cases, merging files

5. GRAPHS: Creating anad editing graphs and charts

 

IBM SPSS STATISTICS BASE MODULE

6. FREQUENCIES: Frequencies, bar charts, histograms, percentiles

7. DESCRIPTIVE Statistics: Measures of central tendency, variability, deviation from normality, size, and stability

8. CROSSTABULATION and Chi-Square Analyses

9. The MEANS Procedure

10. Bivariate CORRELATION: Bivariate correlations, partial correlations, and the correlation matrix

11. The T TEST Procedure: Independent-samples, paired-samples, and one-sample tests

12. The One-Way ANOVA Procedure: One-Way Analysis of Variance

13. General Linear Models: Two-Way Analysis of Variance

14. General Linear Models: Three-Way Analysis of Variance and the influence of covariates

15. Simple Linear REGRESSION

16. MULTIPLE REGRESSION ANALYSIS

17. NONPARAMETRIC Procedures

18. RELIABILITY ANALYSIS: Coefficient alpha and split-half reliability

19. MULTIDIMENSIONAL SCALING

20. FACTOR ANALYSIS

21. CLUSTER ANALYSIS
22. DISCRIMINANT ANALYSIS

 

IBM SPSS REGRESSION AND ADVANCED STATISTICS MODULES

23. General Linear Models: MANOVA and MANCOVA Multivariate Analysis of Variance and Covariance

24. General Linear Models: Repeated-Measures MANOVA: Multivariate Analysis of Variance with repeated measures and within-subjects factors

25. LOGISTIC REGRESSION

26. Hierarchical LOGLINEAR MODELS

27. General LOGLINEAR MODELS

28. RESIDUALS: Analyzing left-over variance

 

Data Files

Glossary

References

Index

 

Rewards Program

Write a Review