Introduction to SPSS statistics in psychology : for version 19 and earlier

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 statistics3   Describing variables: Tables4   Describing variables:Diagrams5   Describing variables numerically: Averages, variation and spread6   Shapes of distributions of scores7   Standard deviation: The standard unit of measurement in statistics8   Relationships between two or more variables: Tables9   Relationships between two or more variables: Diagrams10   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 scores14   The t-test: Comparing two groups of unrelated/uncorrelated scores15   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 ANOVA22   Analysis of variance for correlated scores or repeated measures                  23   Two-way analysis of variance for unrelated/uncorrelated scores                   24   Multiple comparisons in ANOVA25   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 analysis31   Item reliability and inter-rater agreement                                                            32   Stepwise multiple regression33   Simultaneous or standard multiple regression34   Simple mediational analysis                                                                                 35   Hierarchical multiple regression                                                                          36   Moderator analysis with continuous predictor variables           Part 6 Advanced qualitative or nominal techniques   37   Log-linear analysis38   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 variables46   Selecting cases                                                                                                       47   Samples and populations: Generating a random sample                                  48   Inputting a correlation matrix                                                                                49   Checking the accuracy of data inputingPart 8 Linear structural relationship (LISREL) analysis              50   Basics of LISREL and LISREL data entry51 Confirmatory factor analysis with LISREL52 Simple path analysis with measurement error uncorrected                               53   Simple path analysis with latent variables                                                           54   Simple path analysis controlling for alpha reliabilityPart 9 Other statistical procedures55   Statistical power analysis: Sample size estimation56   Meta-analysisAppendix: Some other statistics in SPSS Statistics