Coverart for item
The Resource SPSS for psychologists, Nicola Brace, Richard Kemp, Rosemary Snelgar

SPSS for psychologists, Nicola Brace, Richard Kemp, Rosemary Snelgar

Label
SPSS for psychologists
Title
SPSS for psychologists
Statement of responsibility
Nicola Brace, Richard Kemp, Rosemary Snelgar
Creator
Contributor
Subject
Language
eng
Cataloging source
UKMGB
http://library.link/vocab/creatorName
Brace, Nicola
Illustrations
illustrations
Index
index present
Literary form
non fiction
http://library.link/vocab/relatedWorkOrContributorDate
1960-
http://library.link/vocab/relatedWorkOrContributorName
  • Kemp, Richard
  • Snelgar, Rosemary
http://library.link/vocab/subjectName
  • Psychology
  • Psychometrics
Label
SPSS for psychologists, Nicola Brace, Richard Kemp, Rosemary Snelgar
Instantiates
Publication
Note
Includes index
Contents
  • Ch. 1.
  • Introduction.
  • p. 1
  • Sect. 1.
  • Psychological research and SPSS.
  • p. 3
  • Sect. 2.
  • Guide to the statistical tests covered.
  • p. 14
  • Sect. 3.
  • Working with SPSS.
  • p. 15
  • Sect. 4.
  • Starting SPSS.
  • p. 17
  • Sect. 5.
  • How to exit SPSS.
  • p. 20
  • Sect. 6.
  • Some useful option settings in SPSS.
  • p. 21
  • Ch. 2.
  • Data entry in SPSS.
  • p. 23
  • Sect. 1.
  • Data Editor window.
  • p. 25
  • Sect. 2.
  • Defining a variable in SPSS.
  • p. 26
  • Sect.3.
  • Entering data.
  • p. 38
  • Sect. 4.
  • Saving a data file.
  • p. 41
  • Sect. 5.
  • Opening a data file.
  • p. 43
  • Sect. 6.
  • Data entry exercises.
  • p. 45
  • Sect. 7.
  • Answers to data entry exercises.
  • p. 48
  • Ch. 3.
  • Exploring data in SPSS.
  • p. 51
  • Sect. 1.
  • Descriptive statistics.
  • p. 53
  • Sect. 2.
  • Descriptives command.
  • p. 54
  • Sect. 3.
  • Viewer window.
  • p. 58
  • Sect. 4.
  • Frequencies command.
  • p. 62
  • Sect. 5.
  • Explore command.
  • p. 67
  • Sect. 6.
  • Introducing graphing in SPSS.
  • p. 76
  • Sect. 7.
  • Chart Builder.
  • p. 78
  • Sect. 8.
  • Graphboard Template Chooser.
  • p. 84
  • Ch. 4.
  • Data handling.
  • p. 89
  • Sect. 1.
  • introduction to data handling.
  • p. 91
  • Sect. 2.
  • Sorting a file.
  • p. 92
  • Sect. 3.
  • Splitting a file.
  • p. 94
  • Sect. 4.
  • Selecting cases.
  • p. 96
  • Sect. 5.
  • Recoding values.
  • p. 100
  • Sect. 6.
  • Computing new variables.
  • p. 105
  • Sect. 7.
  • Counting values.
  • p. 108
  • Sect. 8.
  • Ranking cases.
  • p. 110
  • Sect. 9.
  • Data file for scales or questionnaires.
  • p. 113
  • Ch. 5.
  • Tests of difference for two sample designs.
  • p. 117
  • Sect. 1.
  • introduction to the t-tests.
  • p. 119
  • Sect. 2.
  • independent t-test.
  • p. 120
  • Sect. 3.
  • paired t-test.
  • p. 129
  • Sect. 4.
  • introduction to the nonparametric equivalents of the t-test.
  • p. 133
  • Sect. 5.
  • Mann-Whitney test.
  • p. 134
  • Sect. 6.
  • Wilcoxon test.
  • p. 137
  • Ch. 6.
  • Tests of correlation.
  • p. 141
  • Sect. 1.
  • introduction to tests of correlation.
  • p. 143
  • Sect. 2.
  • Producing a scattergram.
  • p. 144
  • Sect. 3.
  • Pearson's r. parametric test of correlation.
  • p. 152
  • Sect. 4.
  • Spearman's r. nonparametric test of correlation.
  • p. 156
  • Ch. 7.
  • Tests for nominal data.
  • p. 161
  • Sect. 1.
  • Nominal data and dichotomous variables.
  • p. 163
  • Sect. 2.
  • Chi-square tests versus the chi-square distribution.
  • p. 165
  • Sect. 3.
  • goodness-of-fit chi-square.
  • p. 166
  • Sect. 4.
  • multi-dimensional chi-square.
  • p. 167
  • Sect. 5.
  • McNemar test for repeated measures.
  • p. 180
  • Ch. 8.
  • Analysis of variance.
  • p. 189
  • Sect. 1.
  • introduction to Analysis of Variance (ANOVA).
  • p. 191
  • Sect. 2.
  • One-way between-subjects ANOVA.
  • p. 201
  • Sect. 3.
  • Two-way between-subjects ANOVA.
  • p. 209
  • Sect. 4.
  • One-way within-subjects ANOVA.
  • p. 213
  • Sect. 5.
  • Two-way within-subjects ANOVA.
  • p. 219
  • Sect. 6.
  • Mixed ANOVA.
  • p. 229
  • Sect. 7.
  • Some additional points.
  • p. 235
  • Sect. 8.
  • Planned and unplanned comparisons.
  • p. 238
  • Sect. 9.
  • Nonparametric equivalents to one-way ANOVA: Kruskal Wallis and Friedman.
  • p. 246
  • Ch. 9.
  • Bivariate and Multiple regression.
  • p. 253
  • Sect. 1.
  • introduction to regression.
  • p. 255
  • Sect. 2.
  • Bivariate regression.
  • p. 256
  • Sect. 3.
  • Multiple regression.
  • p. 264
  • Sect.4.
  • Performing a multiple regression on SPSS.
  • p. 273
  • Ch. 10.
  • Analysis of covariance and multivariate analysis of variance.
  • p. 293
  • Sect. 1.
  • introduction to analysis of covariance.
  • p. 295
  • Sect. 2.
  • Performing analysis of covariance on SPSS.
  • p. 299
  • Sect. 3.
  • introduction to multivariate analysis of variance.
  • p. 309
  • Sect. 4.
  • Performing multivariate analysis of variance on SPSS.
  • p. 313
  • Ch. 11.
  • Discriminant analysis and logistic regression.
  • p. 321
  • Sect. 1.
  • Discriminant analysis and logistic regression.
  • p. 323
  • Sect. 2.
  • introduction to discriminant analysis.
  • p. 325
  • Sect. 3.
  • Performing discriminant analysis on SPSS.
  • p. 328
  • Sect. 4.
  • introduction to logistic regression.
  • p. 341
  • Sect. 5.
  • Performing logistic regression on SPSS.
  • p. 342
  • Ch. 12.
  • Factor analysis, and reliability and dimensionality of scales.
  • p. 351
  • Sect. 1.
  • introduction to factor analysis.
  • p. 353
  • Sect. 2.
  • Performing a basic factor analysis on SPSS.
  • p. 363
  • Sect. 3.
  • Other aspects of factor analysis.
  • p. 377
  • Sect. 4.
  • Reliability analysis for scales and questionnaires.
  • p. 382
  • Sect. 5.
  • Dimensionality of scales and questionnaires.
  • p. 388
  • Ch. 13.
  • Beyond the basics.
  • p. 393
  • Sect. 1.
  • Syntax window.
  • p. 395
  • Sect. 2.
  • Option settings in SPSS.
  • p. 402
  • Sect. 3.
  • Getting help in SPSS.
  • p. 404
  • Sect. 4.
  • Printing from SPSS.
  • p. 406
  • Sect. 5.
  • Incorporating SPSS output into other documents and exporting.
  • p. 408
  • Glossary.
  • p. 411
  • References.
  • p. 427
  • Appendix.
  • p. 431
  • Index.
  • p. 465
Control code
ocn795182350
Dimensions
25 cm.
Edition
5th ed.
Extent
xi, 470 p.
Isbn
9781848726000
Other physical details
ill.
Label
SPSS for psychologists, Nicola Brace, Richard Kemp, Rosemary Snelgar
Publication
Note
Includes index
Contents
  • Ch. 1.
  • Introduction.
  • p. 1
  • Sect. 1.
  • Psychological research and SPSS.
  • p. 3
  • Sect. 2.
  • Guide to the statistical tests covered.
  • p. 14
  • Sect. 3.
  • Working with SPSS.
  • p. 15
  • Sect. 4.
  • Starting SPSS.
  • p. 17
  • Sect. 5.
  • How to exit SPSS.
  • p. 20
  • Sect. 6.
  • Some useful option settings in SPSS.
  • p. 21
  • Ch. 2.
  • Data entry in SPSS.
  • p. 23
  • Sect. 1.
  • Data Editor window.
  • p. 25
  • Sect. 2.
  • Defining a variable in SPSS.
  • p. 26
  • Sect.3.
  • Entering data.
  • p. 38
  • Sect. 4.
  • Saving a data file.
  • p. 41
  • Sect. 5.
  • Opening a data file.
  • p. 43
  • Sect. 6.
  • Data entry exercises.
  • p. 45
  • Sect. 7.
  • Answers to data entry exercises.
  • p. 48
  • Ch. 3.
  • Exploring data in SPSS.
  • p. 51
  • Sect. 1.
  • Descriptive statistics.
  • p. 53
  • Sect. 2.
  • Descriptives command.
  • p. 54
  • Sect. 3.
  • Viewer window.
  • p. 58
  • Sect. 4.
  • Frequencies command.
  • p. 62
  • Sect. 5.
  • Explore command.
  • p. 67
  • Sect. 6.
  • Introducing graphing in SPSS.
  • p. 76
  • Sect. 7.
  • Chart Builder.
  • p. 78
  • Sect. 8.
  • Graphboard Template Chooser.
  • p. 84
  • Ch. 4.
  • Data handling.
  • p. 89
  • Sect. 1.
  • introduction to data handling.
  • p. 91
  • Sect. 2.
  • Sorting a file.
  • p. 92
  • Sect. 3.
  • Splitting a file.
  • p. 94
  • Sect. 4.
  • Selecting cases.
  • p. 96
  • Sect. 5.
  • Recoding values.
  • p. 100
  • Sect. 6.
  • Computing new variables.
  • p. 105
  • Sect. 7.
  • Counting values.
  • p. 108
  • Sect. 8.
  • Ranking cases.
  • p. 110
  • Sect. 9.
  • Data file for scales or questionnaires.
  • p. 113
  • Ch. 5.
  • Tests of difference for two sample designs.
  • p. 117
  • Sect. 1.
  • introduction to the t-tests.
  • p. 119
  • Sect. 2.
  • independent t-test.
  • p. 120
  • Sect. 3.
  • paired t-test.
  • p. 129
  • Sect. 4.
  • introduction to the nonparametric equivalents of the t-test.
  • p. 133
  • Sect. 5.
  • Mann-Whitney test.
  • p. 134
  • Sect. 6.
  • Wilcoxon test.
  • p. 137
  • Ch. 6.
  • Tests of correlation.
  • p. 141
  • Sect. 1.
  • introduction to tests of correlation.
  • p. 143
  • Sect. 2.
  • Producing a scattergram.
  • p. 144
  • Sect. 3.
  • Pearson's r. parametric test of correlation.
  • p. 152
  • Sect. 4.
  • Spearman's r. nonparametric test of correlation.
  • p. 156
  • Ch. 7.
  • Tests for nominal data.
  • p. 161
  • Sect. 1.
  • Nominal data and dichotomous variables.
  • p. 163
  • Sect. 2.
  • Chi-square tests versus the chi-square distribution.
  • p. 165
  • Sect. 3.
  • goodness-of-fit chi-square.
  • p. 166
  • Sect. 4.
  • multi-dimensional chi-square.
  • p. 167
  • Sect. 5.
  • McNemar test for repeated measures.
  • p. 180
  • Ch. 8.
  • Analysis of variance.
  • p. 189
  • Sect. 1.
  • introduction to Analysis of Variance (ANOVA).
  • p. 191
  • Sect. 2.
  • One-way between-subjects ANOVA.
  • p. 201
  • Sect. 3.
  • Two-way between-subjects ANOVA.
  • p. 209
  • Sect. 4.
  • One-way within-subjects ANOVA.
  • p. 213
  • Sect. 5.
  • Two-way within-subjects ANOVA.
  • p. 219
  • Sect. 6.
  • Mixed ANOVA.
  • p. 229
  • Sect. 7.
  • Some additional points.
  • p. 235
  • Sect. 8.
  • Planned and unplanned comparisons.
  • p. 238
  • Sect. 9.
  • Nonparametric equivalents to one-way ANOVA: Kruskal Wallis and Friedman.
  • p. 246
  • Ch. 9.
  • Bivariate and Multiple regression.
  • p. 253
  • Sect. 1.
  • introduction to regression.
  • p. 255
  • Sect. 2.
  • Bivariate regression.
  • p. 256
  • Sect. 3.
  • Multiple regression.
  • p. 264
  • Sect.4.
  • Performing a multiple regression on SPSS.
  • p. 273
  • Ch. 10.
  • Analysis of covariance and multivariate analysis of variance.
  • p. 293
  • Sect. 1.
  • introduction to analysis of covariance.
  • p. 295
  • Sect. 2.
  • Performing analysis of covariance on SPSS.
  • p. 299
  • Sect. 3.
  • introduction to multivariate analysis of variance.
  • p. 309
  • Sect. 4.
  • Performing multivariate analysis of variance on SPSS.
  • p. 313
  • Ch. 11.
  • Discriminant analysis and logistic regression.
  • p. 321
  • Sect. 1.
  • Discriminant analysis and logistic regression.
  • p. 323
  • Sect. 2.
  • introduction to discriminant analysis.
  • p. 325
  • Sect. 3.
  • Performing discriminant analysis on SPSS.
  • p. 328
  • Sect. 4.
  • introduction to logistic regression.
  • p. 341
  • Sect. 5.
  • Performing logistic regression on SPSS.
  • p. 342
  • Ch. 12.
  • Factor analysis, and reliability and dimensionality of scales.
  • p. 351
  • Sect. 1.
  • introduction to factor analysis.
  • p. 353
  • Sect. 2.
  • Performing a basic factor analysis on SPSS.
  • p. 363
  • Sect. 3.
  • Other aspects of factor analysis.
  • p. 377
  • Sect. 4.
  • Reliability analysis for scales and questionnaires.
  • p. 382
  • Sect. 5.
  • Dimensionality of scales and questionnaires.
  • p. 388
  • Ch. 13.
  • Beyond the basics.
  • p. 393
  • Sect. 1.
  • Syntax window.
  • p. 395
  • Sect. 2.
  • Option settings in SPSS.
  • p. 402
  • Sect. 3.
  • Getting help in SPSS.
  • p. 404
  • Sect. 4.
  • Printing from SPSS.
  • p. 406
  • Sect. 5.
  • Incorporating SPSS output into other documents and exporting.
  • p. 408
  • Glossary.
  • p. 411
  • References.
  • p. 427
  • Appendix.
  • p. 431
  • Index.
  • p. 465
Control code
ocn795182350
Dimensions
25 cm.
Edition
5th ed.
Extent
xi, 470 p.
Isbn
9781848726000
Other physical details
ill.

Library Locations

    • Sydney Jones LibraryBorrow it
      Chatham Street, Liverpool, L7 7BD, GB
      53.403069 -2.963723
Processing Feedback ...