Understanding correlation matrices Correlation matrices (along with their unstandardized counterparts covariance matrices) underlie much of the statistical machinery in common use today. A correlation matrix is more than a matrix filled with correlation coefficients. The value of one coefficient in the matrix puts constraints on the values of the others and this is a major theme of the volume. The volume is written accessibly and key points are illustrated with a wide range of lively examples including correlations between intelligence measured at different ages through adolescence; correlations between public health expenditures health life expectancy adult mortality and other country characteristics; correlations between wellbeing and state level vital statistics; correlations between the racial composition of cities and professional sports teams; and correlations between childbearing intentions and childbearing outcomes over the reproductive life course