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Full Description
Introduction to SPSS in Psychology, 7th edition is the essential step by step guide to SPSS for students taking their first course in statistics. This well-established text provides a clear and comprehensive coverage of how to carry out statistical analyses using SPSS. Full colour SPSS screenshots, clear explanation and a wide ranging coverage make it the perfect companion for students who want to be able to analyse data with confidence.
Contents
Part 1 Introduction to SPSS
1 Brief introduction to statistics
2 Basics of SPSS data entry and statistical analysis
Part 2 Descriptive statistics
3 Describing variables: Tables
4 Describing variables: Diagrams
5 Describing variables numerically: Averages, variation and spread
6 Shapes of distributions of scores
7 Relationships between two or more variables: Tables
8 Relationships between two or more variables: Diagrams
9 Correlation coefficients: Pearson's correlation and Spearman's rho
10 Regression: Prediction with precision
Part 3 Significance testing and basic inferential tests
11 Related t-test: Comparing two samples of related/correlated/paired scores
12 Unrelated t-test: Comparing two groups of unrelated/uncorrelated/independent scores
13 Confidence intervals
14 Chi-square: Differences between unrelated samples of frequency data
15 McNemar's test: Differences between related samples of frequency data
16 Ranking tests for two groups: Non-parametric statistics
17 Ranking tests for three or more groups: Non-parametric statistics
Part 4 Analysis of variance
18 Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA
19 Analysis of variance for one-way correlated scores or repeated measures
20 Two-way analysis of variance for unrelated/uncorrelated scores
21 Multiple comparison in ANOVA
22 Analysis of variance for two-way correlated scores or repeated measures
23 Two-way mixed analysis of variance (ANOVA)
24 Analysis of covariance (ANCOVA)
25 Multivariate analysis of variance (MANOVA)
Part 5 More advanced statistics
26 Partial correlation
27 Factor analysis
28 Item reliability and inter-rater agreement
29 Stepwise multiple regression
30 Simultaneous or standard multiple regression
31 Simple mediational analysis
32 Hierarchical multiple regression
33 Log-linear analysis
34 Meta-analysis
Part 6 Data handling procedures
35 Missing values
36 Recoding values
37 Computing a scale score with some values missing
38 Computing a new group variable from existing group variables
39 Selecting cases
40 Reading ASCII or text files into the Data Editor
