Introduction to SPSS in Psychology

<ul> <li><strong>&nbsp;Part 1 Introduction to SPSS</strong> </li> <li>1 Brief introduction to statistics </li> <li>2 Basics of SPSS data entry and statistical analysis </li> <li><strong>Part 2 Descriptive statistics</strong> </li> <li>3 Describing variables: Tables </li> <li>4 Describing variables: Diagrams </li> <li>5 Describing variables numerically: Averages, variation and spread </li> <li>6 Shapes of distributions of scores </li> <li>7 Relationships between two or more variables: Tables </li> <li>8 Relationships between two or more variables: Diagrams </li> <li>9 Correlation coefficients: Pearson's correlation and Spearman's rho </li> <li>10 Regression: Prediction with precision </li> <li><strong>Part 3 Significance testing and basic inferential tests</strong> </li> <li>11 Related t-test: Comparing two samples of related/correlated/paired scores </li> <li>12 Unrelated t-test: Comparing two groups of unrelated/uncorrelated/independent scores </li> <li>13 Confidence intervals </li> <li>14 Chi-square: Differences between unrelated samples of frequency data </li> <li>15 McNemar's test: Differences between related samples of frequency data </li> <li>16 Ranking tests for two groups: Non-parametric statistics </li> <li>17 Ranking tests for three or more groups: Non-parametric statistics </li> <li><strong>Part 4 Analysis of variance</strong> </li> <li>18 Analysis of variance (ANOVA): One-way unrelated or uncorrelated ANOVA </li> <li>19 Analysis of variance for one-way correlated scores or repeated measures </li> <li>20 Two-way analysis of variance for unrelated/uncorrelated scores </li> <li>21 Multiple comparison in ANOVA </li> <li>22 Analysis of variance for two-way correlated scores or repeated measures </li> <li>23 Two-way mixed analysis of variance (ANOVA) </li> <li>24 Analysis of covariance (ANCOVA) </li> <li>25 Multivariate analysis of variance (MANOVA) </li> <li><strong>Part 5 More advanced statistics</strong> </li> <li>26 Partial correlation </li> <li>27 Factor analysis </li> <li>28 Item reliability and inter-rater agreement </li> <li>29 Stepwise multiple regression </li> <li>30 Simultaneous or standard multiple regression </li> <li>31 Simple mediational analysis </li> <li>32 Hierarchical multiple regression </li> <li>33 Log-linear analysis </li> <li>34 Meta-analysis </li> <li><strong>Part 6 Data handling procedures</strong> </li> <li>35 Missing values </li> <li>36 Recoding values </li> <li>37 Computing a scale score with some values missing </li> <li>38 Computing a new group variable from existing group variables </li> <li>39 Selecting cases </li> <li>40 Reading ASCII or text files into the Data Editor </li> </ul>