This book presents the thesis that many ills of today's society (obesity, mental illness, rates of drug abuse, ...) can be attributed to large income inequality. The authors make this point using two-dimensional scatter plots, with income inequality on the x-axis, the prevalence of some form of social ill on the y-axis, and dots in the plot representing individual countries. These plots generally show a positive correlation between income inequality and various social ills.

As a statistician, I would like to comment on the soundness such argumentation: unfortunately virtually all graphs are plagued be a confusion of correlation with causation.

Reviewer then explains correlation and causation. I could claim "inequality is good" using the same methods. I'd argue inequality is immaterial but does tend to be correlated with poverty, which is what we should focus on.

Not to be outright dismissive (I should read the book), but this is a problem in social sciences in general. I think software simulations would be a lot more useful at this point than scatterplots comparing two variables used by so many economists today. I think I've read about people starting to do that in various areas, not sure about how prevalent it is in economic modelling. AFAIK not very.