SPSS for Windows step by step
Subtitle: a simple guide and reference, 17.0 update
By: Darren George, Paul Mallery
Contributors: Mallery, Paul, 1966-
Edition: 10th ed.
Publisher: Allyn & Bacon
Published: 2010
Place of publication: Boston
Language: eng
Number of pages: 386
ISBN-13: 9780205755615
Notes: Includes bibliographical references and index.
Table of contents: title: An overview of SPSS for Windows step by step; title: SPSS Windows processes: mouse and keyboard processing, frequently-used dialog boxes, editing output, printing results, the Options option; title: Creating and editing a data file; title: Managing data: listing cases, replacing missing values, computing new variables, recoding variables, exploring data, selecting cases, sorting cases, merging files; title: Graphs: creating and editing graphs and charts; title: PASW statistics base module.  Frequencies: frequencies, bar charts, histograms, percentiles ; Descriptive statistics: measures of central tendency, variability, deviation from normality, size, and stability ; Crosstabulation and chi-square (x²) analyses ; The Means procedure ; Bivariate correlation: bivariate correlations, partial correlations, and the correlation matrix ; The T test procedure: independent-samples, paired-samples, and one-sample tests ; The one-way ANOVA procedure: one-way analysis of variance ; General linear models: two-way analysis of variance ; General linear models: three-way analysis of variance and the influence of covariates ; Simple linear regression ; Multiple regression analysis ; Nonparametric procedures ; Reliability analysis: coefficient alpha and split-half reliability ; Multidimensional scaling ; Factor analysis ; Cluster analysis ; Discriminant analysis; title: PASW regression and advanced statistics modules.  General linear models: MANOVA and MANCOVA multivariate analysis of variance and covariance ; General linear models: repeated-measures MANOVA: multivariate analysis of variance with repeated measures and within-subjects factors ; Logistic regression ; Hierarchical loglinear models ; General loglinear models ; Residuals: analyzing left-over variance; title: Data files; title: Glossary.