It's difficult to fathom how the authors interpret the data on page 14 as *not* supporting the hypothesis that there is a male/female variance ratio of about 1.1. Figure 1A is a bell-like curve which is clearly centered around 1.1. In Figure 1B, almost all of the points are below the 1:1 line, whereas if you plot a 1.1:1 line, its a perfect fit for the data. In Figure 1C, the x value where the regression line intersects a zero gender gap (i.e. no evidence of cultural bias), is at a variance ratio of about 1.1. All of the evidence the authors present points to an underlying variance ratio near 1.1, yet somehow they conclude the opposite.

I'm pretty sure that god is not the gold standard when it comes to PageRank. Yup: god — top hit, wikipedia.

;-)

I'm a data scientist at company that is big enough to have a six-person data science team. Our CTO bought the data science team all copies of this book (mine is sitting on my desk right now). The best thing about this book is the cover. Which is not to say that the book is terrible —the cover is a really pretty picture of a kiwi. The only chapter in this book that was really interesting was Chapter 5, "Information Platforms and the Rise of the Data Scientist", by Jeff Hammerbacher, who edited the book. The rest is pretty fluffy. Nice easy reading, but nothing really useful or all that interesting.

Mod up parent. I was going to point out the same thing. How the heck could this not be causation?