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Understanding Statistics in Psychology with SPSS 7^th 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

o   Key concept boxes detailing important terms

o   Focus on sections exploring complex topics in greater depth

o   â€?Explaining statistics sections clarify important statistical concepts’.

Understanding Statistics in Psychology with SPSS

• 1 Why statistics?
• Part 1 Descriptive statistics
• 2 Some basics: Variability and measurement
• 3 Describing variables: Tables and diagrams
• 4 Describing variables numerically: Averages, variation and spread
• 5 Shapes of distributions of scores
• 6 Standard deviation and z-scores: Standard unit of measurement in statistics
• 7 Relationships between two or more variables: Diagrams and tables
• 8 Correlation coefficients: Pearson’s correlation and Spearman’s rho
• 9 Regression: Prediction with precision
• Part 2 Significance testing
• 10 Samples from populations
• 11 Statistical significance for the correlation coefficient: Practical introduction to statistical inference
• 12 Standard error: Standard deviation of the means of samples
• 13 Related t-test: Comparing two samples of related/correlated/paired scores
• 14 Unrelated t-test: Comparing two samples of unrelated/ uncorrelated/independent scores
• 15 What you need to write about your statistical analysis
• 16 Confidence intervals
• 17 Effect size in statistical analysis: Do my findings matter?
• 18 Chi-square: Differences between samples of frequency data
• 19 Probability
• 20 One-tailed versus two-tailed significance testing
• 21 Ranking tests: Nonparametric statistics
• Part 3 Introduction to analysis of variance
• 22 Variance ratio test: F-ratio to compare two variances
• 23 Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA
• 24 ANOVA for correlated scores or repeated measures
• 25 Two-way or factorial ANOVA for unrelated/uncorrelated scores: Two studies for the price of one?
• 26 Multiple comparisons in ANOVA: A priori and post hoc tests
• 27 Mixed-design ANOVA: Related and unrelated variables together
• 28 Analysis of covariance (ANCOVA): Controlling for additional variables
• 29 Multivariate analysis of variance (MANOVA)
• 30 Discriminant (function) analysis – especially in MANOVA
• 31 Statistics and analysis of experiments
• Part 4 More advanced correlational statistics
• 32 Partial correlation: Spurious correlation, third or confounding variables, suppressor variables
• 33 Factor analysis: Simplifying complex data
• 34 Multiple regression and multiple correlation
• 35 Path analysis
• 36 Analysis of a questionnaire/survey project
• Part 5 Assorted advanced techniques
• 37 Meta-analysis: Combining and exploring statistical findings from previous research
• 38 Reliability in scales and measurement: Consistency and agreement
• 39 Influence of moderator variables on relationships between two variables
• 40 Statistical power analysis: Getting the sample size right
• Part 6 Advanced qualitative or nominal techniques
• 41 Log-linear methods: Analysis of complex contingency tables
• 42 Multinomial logistic regression: Distinguishing between several different categories or groups
• 43 Binomial logistic regression
• Appendices
• Glossary
• References
• Index