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SPSS for Psychologists

SPSS for Psychologists

Nicola Brace | Rosemary Snelgar | Richard Kemp

(2016)

Additional Information

Book Details

Abstract

The bestselling guide to SPSS is back.

SPSS for Psychologists is the definitive guide to IBM SPSS. Combining unbeatable coverage with a tested, accessible style, this book provides you with a step-by-step guide to the software and equips you with the knowledge you need to succeed. Whether you're new to statistical analysis, or a more experienced researcher in need of a refresher, this book is an essential resource that you'll return to time and time again.
The sixth edition of SPSS for Psychologists (and everybody else):
- Is compliant with SPSS version 23, and backward-compatible with previous versions of the software
- Has been fully updated and revised throughout, and now provides coverage of syntax
- Features a brand-new, reader-friendly layout that makes navigation even easier than before
- Offers a sophisticated range of video tutorials, along with sample exercises, datasets and other useful resources
Nicola Brace is Senior Lecturer in Psychology at the Open University, UK.
 
Richard Kemp is Associate Professor in Psychology at the University of New South Wales, Australia.
 
Rosemary Snelgar is Principal Lecturer in Psychology at the University of Westminster, UK.

I found the book very clear and intuitive in both its layout and writing style. The step-by-step walkthroughs and figures will prove invaluable to both undergraduate and postgraduate Psychology students alike in trying to navigate SPSS. The writing style reaches a good balance of being not overly technical or patronising to the reader!' – Dr Jonathan Catling, University of Birmingham, UK

'As always, a thorough guide for undergraduate students. Lots of illustrations with useful comments that will make it easier for students to understand why they are doing what they are doing, and pitched at the right level – academic rigour perfectly balanced with student-friendly language. The authors have a knack for making complex concepts accessible. The complementary exercises are an added asset.' – Dr Ana Fernández, Canterbury Christ Church University, UK

'An excellent introductory text which provides essential support for beginners and experienced users of SPSS. The style is clear, coherent, and authoritative. The narrative helpfully guides readers through all aspects of SPSS. Alongside data sets, the authors provide detailed examples, thorough explanations, helpful annotations, and guidance on result reporting. The range of tests included is impressive. These features make SPSS for Psychologists a superior and essential text for both student and instructors.' – Dr Neil Dagnall, Manchester Metropolitan University, UK

'This is the perfect textbook for students who lack confidence in using SPSS. The clear way it is written and the clearly labelled screenshots make this a must.' - Noella McAra, Abertay University

Table of Contents

Section Title Page Action Price
Cover Cover
Contents vii
Preface x
Acknowledgements xiii
Chapter 1 Introduction 1
Section 1: Psychological research and SPSS 1
Section 2: Guide to the statistical tests covered 11
Section 3: Working with SPSS 12
Section 4: Starting SPSS 14
Section 5: How to exit from SPSS 16
Chapter 2 Data entry in SPSS 18
Section 1: The Data Editor window 18
Section 2: Defining a variable in SPSS 19
Section 3: Entering data 30
Section 4: Saving a data file 32
Section 5: Opening a data file 34
Section 6: Data entry exercises 36
Section 7: Answers to data entry exercises 38
Section 8: Checking and cleaning data files 40
Chapter 3 Exploring and cleaning data in SPSS 42
Section 1: Descriptive statistics 42
Section 2: The Descriptives command 43
Section 3: The Viewer window 46
Section 4: The frequencies command 50
Section 5: The Explore command 54
Section 6: Using descriptive statistics to check your data 62
Section 7: Introducing graphing in SPSS 66
Section 8: Chart Builder 68
Section 9: Graphboard Template Chooser 73
Chapter 4 Data handling 78
Section 1: An introduction to data handling 78
Section 2: Sorting a file 79
Section 3: Splitting a file 81
Section 4: Selecting cases 83
Section 5: Recoding values 87
Section 6: Computing new variables 92
Section 7: Counting values 95
Section 8: Ranking cases 96
Section 9: Data transformation 99
Section 10: Data file for scales or questionnaires 105
Chapter 5 Tests of difference for oneand two-sample designs 108
Section 1: An introduction to t-tests 108
Section 2: The one-sample t-test 109
Section 3: The independent t-test 112
Section 4: The paired t-test 119
Section 5: An introduction to nonparametric tests of difference 124
Section 6: The Mann–Whitney test 124
Section 7: The Wilcoxon test 127
Chapter 6 Tests of correlation and bivariate regression 132
Section 1: An introduction to tests of correlation 132
Section 2: Producing a scattergram 133
Section 3: Pearson’s r : parametric test of correlation 141
Section 4: Spearman’s rs: nonparametric test of correlation 145
Section 5: Comparing the strength of correlation coefficients 148
Section 6: Brief introduction to regression 151
Section 7: Bivariate regression 152
Chapter 7 Tests for nominal data 161
Section 1: Nominal data and dichotomous variables 161
Section 2: Chi-square test versus the chi-square distribution 163
Section 3: The goodness of fit chi-square 163
Section 4: the multidimensional chi-square 164
Section 5: The McNemar test for repeated measures 179
Chapter 8 Analysis of variance 187
Section 1: An introduction to analysis of variance (ANOVA) 187
Section 2: One-way between-subjects ANOVA, planned and unplanned comparisons, and nonparametric equivalent 198
Section 3: Two-way between-subjects ANOVA 213
Section 4: One-way within-subjects ANOVA, planned and unplanned comparisons, and nonparametric equivalent 221
Section 5: Two-way within-subjects ANOVA 231
Section 6: Mixed ANOVA 240
Chapter 9 Multiple regression 249
Section 1: An introduction to multiple regression 249
Section 2: Standard or simultaneous method of multiple regression 258
Section 3: Sequential or hierarchical method of multiple regression 266
Section 4: Statistical methods of multiple regression 272
Chapter 10 Analysis of covariance and multivariate analysis of variance 276
Section 1: An introduction to analysis of covariance 276
Section 2: Performing analysis of covariance on SPSS 279
Section 3: An introduction to multivariate analysis of variance 288
Section 4: Performing multivariate analysis of variance on SPSS 291
Chapter 11 Discriminant analysis and logistic regression 299
Section 1: Discriminant analysis and logistic regression 299
Section 2: An introduction to discriminant analysis 301
Section 3: Performing discriminant analysis using SPSS 303
Section 4: An introduction to logistic regression 314
Section 5: Performing logistic regression on SPSS 315
Chapter 12 Factor analysis, and reliability and dimensionality of scales 322
Section 1: An introduction to factor analysis 322
Section 2: Performing a basic factor analysis using SPSS 331
Section 3: Other aspects of factor analysis 343
Section 4: Reliability analysis for scales and questionnaires 348
Section 5: Dimensionality of scales and questionnaires 353
Chapter 13 Using syntax and other useful features of SPSS 358
Section 1: The Syntax window 358
Section 2: Syntax examples 366
Section 3: Getting help in SPSS 369
Section 4: Option settings in SPSS 373
Section 5: Printing from SPSS 375
Section 6: Incorporating SPSS output into other documents 377
Section 7: SPSS and Excel: importing and exporting data files 379
Appendix 382
Glossary 395
References 413
Index 415