Introduction to SPSS in Psychology : for version 19 and earlier / Dennis Howitt and Duncan Cramer.

Previous ed.: 2008.

Includes index.

Key differences between SPSS Statistics 19 and earlier versions Part 1 Introduction to SPSS Statistics 1 A brief introduction to statistics 2 Basics of SPSS Statistics 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 Standard deviation: The standard unit of measurement in statistics 8 Relationships between two or more variables: Tables 9 Relationships between two or more variables: Diagrams 10 Correlation coefficients: Pearson\'s correlation and Spearman\'s rho 11 Regression: Prediction with precision Part 3 Significance testing and basic inferential tests 12 Standard error 13 The t-test: Comparing two samples of correlated/related/paired scores 14 The t-test: Comparing two groups of unrelated/uncorrelated scores 15 Confidence intervals 16 Chi-square: Differences between unrelated samples of frequency data 17 McNemar test: Differences between related samples of frequency data 18 Ranking tests for two groups: Non-parametric statistics 19 Rts for three or more groups: Non-parametric statistics Part 4 Analysis of variance 20 The variance ratio test: Using the F-ratio to compare two variances 21 Analysis of variance (ANOVA): Introduction to the one-way unrelated or uncorrelated ANOVA 22 Analysis of variance for correlated scores or repeated measures 23 Two-way analysis of variance for unrelated/uncorrelated scores 24 Multiple comparisons in ANOVA 25 Two-way mixed analysis of variance (ANOVA) 26 Analysis of covariance (ANCOVA) 27 Multivariate analysis of variance (MANOVA) 28 Discriminant function analysis (for MANOVA) Part 5 More advanced correlational statistics 29 Partial correlation 30 Factor analysis 31 Item reliability and inter-rater agreement 32 Stepwise multiple regression 33 Simultaneous or standard multiple regression 34 Simple mediational analysis 35 Hierarchical multiple regression 36 Moderator analysis with continuous predictor variables Part 6 Advanced qualitative or nominal techniques 37 Log-linear analysis 38 Multinomial logistic regression 39 Binomial logistic regression Part 7 Data handling procedures 40 Reading ASCII or text files into the Data Editor 41 Missing values 42 Recoding values 43 Computing a scale score with no missing values 44 Computing a scale score with some values missing 45 Computing a new group variable from existing group variables 46 Selecting cases 47 Samples and populations: Generating a random sample 48 Inputting a correlation matrix 49 Checking the accuracy of data inputing Part 8 Linear structural relationship (LISREL) analysis 50 Basics of LISREL and LISREL data entry 51 Confirmatory factor analysis with LISREL 52 Simple path analysis with measurement error uncorrected 53 Simple path analysis with latent variables 54 Simple path analysis controlling for alpha reliability Part 9 Other statistical procedures 55 Statistical power analysis: Sample size estimation 56 Meta-analysis Appendix: Some other statistics in SPSS Statistics

Using this book, students should quickly master statistical analysis with SPSS. Screenshots of all the steps for each statistical technique build students' confidence when performing their own analysis.