Understanding The New Statistics is about understanding statistics and applying statistical methods that are not new at all. They are just under-used in the social and behavioral sciences.
It is all about abandoning Null Hypothesis Significance Tests and replacing them with the more informative Effect Sizes and Confidence Intervals. Targeted at students as a complementary text to their standard textbook the most important and distinguishing feature of Cumming’s book is its attempt to create intuition for the variability of data and derived statistics. The many excercises that rely on simulating (small) data (sets) and observing the variability of summary statistics are a great tool for understanding the properties and interpretation of these statistics.
Nevertheless, beyond facilitating said intuition the text has little additional value. The theory, the necessary math is often not presented. The exercises and indeed much of the book rely on a (free) proprietary software that I cannot use since it depends on another commercial software that I don’t own and would have never used for statistics (excel). Therefore, much of the text remained cryptic. I would have preferred an open source approach, maybe an R package.
Further, for a text that is advocating replacing NHST with substantial statistics on effect sizes and uncertainty there are too many asterisks signifying different levels of statistical significance. More surprising was, however, the absence of any glimpse at Bayesian methods that would fit the bill perfectly, showing likely effect sizes and their corresponding uncertainty. In the context of meta-analysis I would have expected an updating of our beliefs, a Bayesian aggregation of the accumulating evidence. Instead, the text remains 100% frequentist.
In the end, the text is maybe not for the student but for the teacher. And maybe the text should not be read for its content in a narrower sense but for the ideas on pedagogy on how to teach introductory statistics.