Methods

The overall picture: means, spread, missing cells.

• Descriptive statistics
• Correlation matrix
• Missing value analysis

Test preconditions: is the data normal, are there outliers.

• Normality tests
• Outlier detection

Do two variables move together, in which direction and how strongly.

• Pearson correlation
• Spearman rank correlation
• Kendall's tau-b

Non-numeric variables: frequency, cross-tabs, independence.

• Chi-square test of independence
• Cross-tabulation
• Frequency distribution

Is the difference between two or more groups significant.

• Independent samples t-test
• Paired samples t-test
• One-way ANOVA
• Two-way ANOVA
• ANCOVA
• MANOVA
• MANCOVA
• Repeated measures ANOVA
• Mann-Whitney U
• Wilcoxon signed-rank
• Kruskal-Wallis
• Friedman

Which variables explain an outcome, and by how much.

• Linear regression (OLS)
• Logistic regression

Do the scale items measure the same thing.

• Cronbach's Alpha
• Split-half reliability

The latent dimensions behind many items.

• Exploratory factor analysis (EFA)
• Principal component analysis (PCA)

Segmenting respondents by how similar they are.

• K-means cluster analysis
• Hierarchical cluster analysis

A model of direct and indirect effects between variables.

• Structural equation modelling (SEM)
• Confirmatory factor analysis (CFA)
• Path analysis
• Mediation analysis
• Moderation analysis

Preference data: how much each attribute is worth, which option wins.

• MaxDiff (best-worst scaling)
• Conjoint analysis

Is the sequence random, or is there a pattern.

• Runs test for randomness