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    <subfield code="a">Why statistics? -- Part 1. Descriptive statistics -- Some basics: variability and measurement -- Describing variables: tables and diagrams -- Describing variables numerically: averages, variation and spread -- Shapes of distributions of scores -- Standard deviation and z-scores: standard unit of measurement in statistics -- Relationships between two or more variables: diagrams and tables -- Correlation coefficients: Pearson's correlation and Spearman's rho -- Regression: prediction with precision -- Part 2. Significance testing -- Samples from populations -- Statistical significance for the correlation coefficient: a practical introduction to statistical inference -- Standard error: standard deviation of the means of samples -- Related or paired-samples t-test: comparing two samples of related/correlated/paired scores -- Unrelated or independent-samples t-test: comparing two samples of unrelated/uncorrelated/independent scores -- What you need to write about your statistical analysis -- Confidence intervals -- Effect size in statistical analysis: do my findings matter? -- Chi-square: differences between samples of frequency data -- Probability -- One- versus two-tailed (or -sided) significance testing -- Ranking tests: nonparametric statistics -- Part 3. Introduction to analysis of variance -- Variance ratio test: F-ratio to compare two variances -- Analysis of variance (ANOVA): one-way unrelated or uncorrelated ANOVA -- ANOVA for correlated scores or repeated measures -- Two-way or factorial ANOVA for unrelated/uncorrelated scores: two studies for the price of one? -- Multiple comparisons within ANOVA: a priori and post hoc tests -- Mixed-design ANOVA: related and unrelated variables together -- Analysis of covariance (ANCOVA): controlling for additional variables -- Multivariate analysis of variance (MANOVA) -- Discriminant (function) analysis - especially in MANOVA -- Statistics and analysis of experiments -- Part 4. More advanced correlational statistics -- Partial correlation: spurious correlation, third or confounding variables, suppressor variables -- Factor analysis: simplifying complex data -- Multiple regression and multiple correlation -- Path analysis -- Analysis of a questionnaire/survey project -- Part 5. Assorted advanced techniques -- Meta-analysis: combining and exploring statistical findings from previous research -- Reliability in scales and measurement: consistency and agreement -- Influence of moderator variables on relationships between two variables -- Statistical power analysis: getting the sample size right -- Part 6. Advanced qualitative or nominal techniques -- Log-linear methods: analysis of complex contingency tables -- Multinomial logistic regression: distinguishing between several different categories or groups -- Binomial logistic regression -- Part 7. Bringing things together -- Data mining and big data -- Towards a masterplan: demonstrating statistical competence.</subfield>
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