Understanding Statistics in Psychology with SPSS, 7th Edition

Understanding Statistics in Psychology with SPSS 7th edition, offers students a trusted, straightforward, and engaging way of learning how to carry out statistical analyses and use SPSS with confidence.

Comprehensive and practical, the text is organised by short, accessible chapters, making it the ideal text for undergraduate psychology students needing to get to grips with Statistics in class or independently.

Clear diagrams and full colour screenshots from SPSS make the text suitable for beginners while the broad coverage of topics ensures that students can continue to use it as they progress to more advanced techniques.

Key features

• Now combines coverage of statistics with full guidance on how to use SPSS to analyse data
• Suitable for use with all versions of SPSS
• Examples from a wide range of real psychological studies illustrate how statistical techniques are used in practice
• Includes clear and detailed guidance on choosing tests, interpreting findings and reporting and writing up research
• Student focused pedagogical approach including
• Key concept boxes detailing important terms
• Focus on sections exploring complex topics in greater depth
• Explaining statistics sections clarify important statistical concepts.

Table of Contents

Chapter 1 Why statistics?

Part 1 Descriptive statistics
Chapter 2 Some basics: Variability and measurement
Chapter 3 Describing variables: Tables and diagrams
Chapter 4 Describing variables numerically: Averages, variation and spread
Chapter 5 Shapes of distributions of scores
Chapter 6 Standard deviation and z-scores: Standard unit of measurement in statistics
Chapter 7 Relationships between two or more variables: Diagrams and tables
Chapter 8 Correlation coefficients: Pearson’s correlation and Spearman’s rho
Chapter 9 Regression: Prediction with precision

Part 2 Significance testing
Chapter 10 Samples from populations
Chapter 11 Statistical significance for the correlation coefficient: Practical introduction to statistical inference
Chapter 12 Standard error: Standard deviation of the means of samples
Chapter 13 Related t-test: Comparing two samples of related/correlated/paired scores
Chapter 14 Unrelated t-test: Comparing two samples of unrelated/uncorrelated/independent scores
Chapter 15 What you need to write about your statistical analysis

Part 3 Introduction to analysis of variance
Chapter 22 Variance ratio test: F-ratio to compare two variances
Chapter 23 Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA
Chapter 24 ANOVA for correlated scores or repeated measures
Chapter 25 Two-way or factorial ANOVA for unrelated/uncorrelated scores: Two studies for the price of one?
Chapter 26 Multiple comparisons with in ANOVA: A priori and post hoc tests
Chapter 27 Mixed-design ANOVA: Related and unrelated variables together
Chapter 28 Analysis of covariance (ANCOVA): Controlling for additional variables
Chapter 29 Multivariate analysis of variance (MANOVA)
Chapter 30 Discriminant (function) analysis – especially in MANOVA
Chapter 31 Statistics and analysis of experiments
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art 4 More advanced correlational statistics
Chapter 32 Partial correlation: Spurious correlation, third or confounding variables, suppressor variables
Chapter 33 Factor analysis: Simplifying complex data
Chapter 34 Multiple regression and multiple correlation
Chapter 35 Path analysis
Chapter 36 Analysis of a questionnaire/survey project

Part 5 Assorted advanced techniques
Chapter 37 Meta-analysis: Combining and exploring statistical findings from previous research
Chapter 38 Reliability in scales and measurement: Consistency and agreement
Chapter 39 Influence of moderator variables on relationships between two variables
Chapter 40 Statistical power analysis: Getting the sample size right

Part 6 Advanced qualitative or nominal techniques
Chapter 41 Log-linear methods: Analysis of complex contingency tables
Chapter 42 Multinomial logistic regression: Distinguishing between several different categories or groups
Chapter 43 Binomial logistic regression

Appendix A Testing for excessively skewed distributions
Appendix B1 Large-sample formulae for the nonparametric tests
Appendix B2 Nonparametric tests for three or more groups
Appendix C Extended table of significance for the Pearson correlation coefficient
Appendix D Table of significance for the Spearman correlation coefficient
Appendix E Extended table of significance for the t-test
Appendix F Table of significance for chi-square
Appendix G Extended table of significance for the sign test
Appendix H Table of significance for the Wilcoxon matched pairs test
Appendix I Tables of significance for the Mann–Whitney U-test
Appendix J Tables of significance values for the F-distribution
Appendix K Table of significance values for t when making multiple t-tests