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About this book

Psychology students can find statistical analysis a challenging and complex task and, in order to master the techniques and complete their assignments and projects, they need to have a sound understanding of IBM SPSS. This practical book is designed to introduce students to SPSS in an accessible yet rigorous way, so that they can feel confident with a variety of essential tasks: from data entry to completing a t-test in statistical analyses you need for your course or research.
With handy screenshots throughout, students are guided through the process from start to finish. This ‘end to end’ approach will enable both undergraduate psychology students and those more experienced in statistical analysis to get started and then master this powerful software tool.


Table of Contents

Chapter 1. Introduction

Abstract
In this chapter
  • Psychological research and SPSS
  • Guide to the statistical tests covered
  • Working with SPSS
  • Starting SPSS
  • How to exit from SPSS
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 2. Data entry in SPSS

Abstract
In this chapter
  • The Data Editor window
  • Defining a variable in SPSS
  • Entering data
  • Saving a data file
  • Opening a data file
  • Data entry exercises
  • Answers to data entry exercises
  • Checking and cleaning data files
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 3. Exploring and cleaning data in SPSS

Abstract
In this chapter
  • Descriptive statistics
  • The Descriptives command
  • The Viewer window
  • The Frequencies command
  • The Explore command
  • Using descriptive statistics to check your data
  • Introducing graphing in SPSS
  • Chart Builder
  • Graphboard Template Chooser
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 4. Data handling

Abstract
In this chapter
  • An introduction to data handling
  • Sorting a file
  • Splitting a file
  • Selecting cases
  • Recoding values
  • Computing new variables
  • Counting values
  • Ranking cases
  • Data transformation
  • Data file for scales or questionnaires
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 5. Tests of difference for one- and two-sample designs

Abstract
In this chapter
  • An introduction to t-tests
  • The one-sample t-test
  • The independent t-test
  • The paired t-test
  • An introduction to nonparametric tests of difference
  • The Mann—Whitney test
  • The Wilcoxon test
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 6. Tests of correlation and bivariate regression

Abstract
In this chapter
  • An introduction to tests of correlation
  • Producing a scattergram
  • Pearson’s r: parametric test of correlation
  • Spearman’s r s : nonparametric test of correlation
  • Comparing the strength of correlation coefficients
  • Brief introduction to regression
  • Bivariate regression
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 7. Tests for nominal data

Abstract
In this chapter
  • Nominal data and dichotomous variables
  • Chi-square test versus the chi-square distribution
  • The goodness of fit chi-square
  • The multidimensional chi-square
  • The McNemar test for repeated measures
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 8. Analysis of variance

Abstract
In this chapter
  • An introduction to analysis of variance (ANOVA)
  • One-way between-subjects ANOVA, planned and unplanned comparisons, and nonparametic equivalent
  • Two-way between-subjects ANOVA
  • One-way within-subjects ANOVA, planned and unplanned comparisons, and nonparametric equivalent
  • Two-way within-subjects ANOVA
  • Mixed ANOVA
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 9. Multiple regression

Abstract
In this chapter
  • An introduction to multiple regression
  • Standard or simultaneous method of multiple regression
  • Sequential or hierarchical method of multiple regression
  • Statistical methods of multiple regression
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 10. Analysis of covariance and multivariate analysis of variance

Abstract
In this chapter
  • An introduction to analysis of covariance
  • Performing analysis of covariance on SPSS
  • An introduction to multivariate analysis of variance
  • Performing multivariate analysis of variance on SPSS
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 11. Discriminant analysis and logistic regression

Abstract
In this chapter
  • Discriminant analysis and logistic regression
  • An introduction to discriminant analysis
  • Performing discriminant analysis using SPSS
  • An introduction to logistic regression
  • Performing logistic regression on SPSS
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 12. Factor analysis, and reliability and dimensionality of scales

Abstract
In this chapter
  • An introduction to factor analysis
  • Performing a basic factor analysis using SPSS
  • Other aspects of factor analysis
  • Reliability analysis for scales and questionnaires
  • Dimensionality of scales and questionnaires
Nicola Brace, Richard Kemp, Rosemary Snelgar

Chapter 13. Using syntax and other useful features of SPSS

Abstract
In this chapter
  • The Syntax window
  • Syntax examples
  • Getting help in SPSS
  • Option settings in SPSS
  • Printing from SPSS
  • Incorporating SPSS output into other documents
  • SPSS and Excel: importing and exporting data files
Nicola Brace, Richard Kemp, Rosemary Snelgar
Additional information