The review could not capture the many gems within the book so here are some of his best bits of writing.
Compound metrics are to base metrics what molecules are to atoms. Just like as few as seven atoms (oxygen, hydrogen, helium, carbon, sodium, chlorine and sulfur) can produce trillions of trillions of molecules and chemical compounds (a challenge for analytical and computational chemists designing molecules to cure cancer), the same combinatorial explosion takes place as you move from base to compound metrics.p110
Very nice but Helium is a noble gas and does not form compounds on Earth although it might do in special environments. His PhD is not in chemistry
Apparently he also thinks that an app for pricing in amusement parks would be a good venture
Increase prices and find optimum prices. (Obviously, it must be higher than current prices due to the extremely large and dense crowds visiting these parks, creating huge waiting lines and other hazards everywhere - from the few restaurants and bathrooms to the attractions).p105
Alternatively they could build more bathrooms and more restaurants and make even more money from the large crowds rather than reducing foot-fall as people go elsewhere. Who are richer the owners of WallMart or the owners of Tiffany's?
This however is the best and saved for page 174
The number of variables is assumed to be high, and the independent variables are highly correlated.What? Wait let me see what the definition of independent variables is. That would be whose variation does NOT depend on the variation of another. That would mean not correlated. This is more than a slight howler this is so elementary that you cannot believe a single thing the author says. He then goes on to do regression in Excel.
On page 189 he talks about the possibility of getting negative variances - this is impossible. On page 190 he talks about the variance being bounded by 1 as a maximum. This is nonsense even with normalised data the variance = 1 V is not <1 as="" he="" nbsp="" p="" states.="">1>