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SPSS for Windows step by step a simple guide and reference, 10.0 update Darren George, Paul Mallery.

Por: Colaborador(es): Detalles de publicación: Boston Allyn and Bacon c(2001).Edición: 3rd edDescripción: vii, 371 p. ill. 28 cmISBN:
  • 0205331270(pbk.)
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This book is designed to simplify the process of data analysis using SPSS. The clarity of this book is established by extensive use of screen shots (more than 200), clear writing, and step-by-step boxes (more than 500) that show how to accomplish any procedure one step at a time. Students, even novices, can independently learn from this comprehensive and straightforward treatment.

Includes bibliographical references (p. [364]-365), a glossary and index.

Tabla de contenidos provista por Syndetics

  • 1. An Overview of SPSS for Windows Step by Step(p. 1)
  • 2. SPSS Windows Processes: Mouse and keyboard processing, frequently-used dialog boxes, editing output, printing results(p. 9)
  • 3. Creating and Editing a Data File(p. 27)
  • 4. Managing Data: Listing cases, replacing missing values, computing new variables, recoding variables, exploring data, selecting cases, sorting cases, merging files(p. 41)
  • 5. Graphs: Creating and editing graphs and charts(p. 65)
  • Base System Module
  • 6. Frequencies: Frequencies, bar charts, histograms, percentiles(p. 73)
  • 7. Descriptive Statistics: Measures of central tendency, variability, deviation from normality, size, and stability(p. 83)
  • 8. Crosstabulation and Chi-Square (x[superscript 2]) Analyses(p. 93)
  • 9. The Means Procedure(p. 103)
  • 10. Bivariate Correlation: Bivariate correlations, partial correlations, and the correlation matrix(p. 111)
  • 11. The T Test Procedure: Independent-samples, paired-samples, and one-sample tests(p. 121)
  • 12. The One-Way Anova Procedure: One-way Analysis of Variance(p. 131)
  • 13. General Linear Models: Two-Way Analysis of Variance(p. 141)
  • 14. General Linear Models: Three-Way Analysis of Variance and the influence of covariates(p. 149)
  • 15. Simple Linear Regression(p. 165)
  • 16. Multiple Regression Analysis(p. 179)
  • 17. Nonparametric Procedures(p. 193)
  • 18. Reliability Analysis: Coefficient alpha ([alpha]) and split-half reliability(p. 207)
  • 19. Multidimensional Scaling(p. 219)
  • 20. Factor Analysis(p. 231)
  • 21. Cluster Analysis(p. 247)
  • 22. Discriminant Analysis(p. 263)
  • Advanced and Regression Modules
  • 23. General Linear Models: Manova and Mancova Multivariate Analysis of Variance and Covariance(p. 279)
  • 24. General Linear Models: Repeated-Measures Manova: Multivariate Analysis of Variance with repeated measures and within-subjects factors(p. 293)
  • 25. Logistic Regression(p. 305)
  • 26. Hierarchical Loglinear Models(p. 317)
  • 27. General Loglinear Models(p. 331)
  • 28. Residuals: Analyzing left-over variance(p. 341)
  • Data Files(p. 349)
  • Glossary(p. 353)
  • References(p. 364)
  • Index(p. 366)
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