Correlation

what r measures and what it does not; Pearson vs Spearman vs Kendall's tau and the rule for choosing; assumptions, especially linearity - always plot first; the scatterplot gallery showing r = 0 with an obvious relationship; the menu path; reading the correlation matrix; interpreting magnitude, and r-squared as shared variance; partial correlation and what controlling actually does; correlation is not causation, stated with a concrete confounding example; APA reporting.