Millions, Billions, Zillions - Brian Kernighan ***

The news is riddled with numbers that we often taken for granted. Brian Kernighan sets out to give us the tools to test numbers in the headlines and see if they really add up. The fact that they often don't is made clear by the range of examples Kernighan gives where a news source has got a value wrong, whether it's out by a factor of a thousand, using the wrong units or impossibly accurate, perhaps due to a spot of calculator work converting one unit to another.

This isn't the first book to take on misleading numbers - as well as the classic How to Lie with Statistics, there was the excellent The Tiger that Isn't. Although Kernighan covers many of the common errors in this slim volume, I didn't get the same sense of fascination here as I did with those earlier titles (particular The Tiger). Kernighan gives us useful tips on checking numbers, but often the examples felt like hard work for numbers it's hard to care too much about (the US's 60 billion barrel oil reserve, for example (actually 60 million)) - carefully choosing your examples in a book like this is really important.

The techniques Kernighan gives, such as scaling numbers to individuals rather than the population as a whole, knowing some basic values and constants, Little's Law, the rule of 72 and approximations of powers of 2 are all great - though I confess I've already forgotten what Little's Law and the rule of 72 are and will have to go back and check. But the book didn't engage me the way that The Tiger that Isn't did (it could be partly that the The Tiger uses more British examples, but it also has a more approachable writing style).

However, books like this are essential in a world where numbers are increasingly used to bamboozle us. This is a very welcome addition to what I hope will be a growing genre.

Hardback:

Kindle:

Using these links earns us commission at no cost to you

Review by Brian Clegg

Comments

Rakhat-Bi Abdyssagin Five Way Interview

Rakhat-Bi Abdyssagin (born in 1999) is a distinguished composer, concert pianist, music theorist and researcher. Three of his piano CDs have been released in Germany. He started his undergraduate degree at the age of 13 in Kazakhstan, and having completed three musical doctorates in prominent Italian music institutions at the age of 20, he has mastered advanced composition techniques. In 2024 he completed a PhD in music at the University of St Andrews / Royal Conservatoire of Scotland (researching timbre-texture co-ordinate in avant- garde music), and was awarded The Silver Medal of The Worshipful Company of Musicians, London. He has held visiting affiliations at the Universities of Oxford, Cambridge and UCL, and has been lecturing and giving talks internationally since the age of 13. His latest book is Quantum Mechanics and Avant Garde Music . What links quantum physics and avant-garde music? The entire book is devoted to this question. To put it briefly, there are many different link...

Should we question science?

I was surprised recently by something Simon Singh put on X about Sabine Hossenfelder. I have huge admiration for Simon, but I also have a lot of respect for Sabine. She has written two excellent books and has been helpful to me with a number of physics queries - she also had a really interesting blog, and has now become particularly successful with her science videos. This is where I'm afraid she lost me as audience, as I find video a very unsatisfactory medium to take in information - but I know it has mass appeal. This meant I was concerned by Simon's tweet (or whatever we are supposed to call posts on X) saying 'The Problem With Sabine Hossenfelder: if you are a fan of SH... then this is worth watching.' He was referencing a video from 'Professor Dave Explains' - I'm not familiar with Professor Dave (aka Dave Farina, who apparently isn't a professor, which is perhaps a bit unfortunate for someone calling out fakes), but his videos are popular and he...

Everything is Predictable - Tom Chivers *****

There's a stereotype of computer users: Mac users are creative and cool, while PC users are businesslike and unimaginative. Less well-known is that the world of statistics has an equivalent division. Bayesians are the Mac users of the stats world, where frequentists are the PC people. This book sets out to show why Bayesians are not just cool, but also mostly right. Tom Chivers does an excellent job of giving us some historical background, then dives into two key aspects of the use of statistics. These are in science, where the standard approach is frequentist and Bayes only creeps into a few specific applications, such as the accuracy of medical tests, and in decision theory where Bayes is dominant. If this all sounds very dry and unexciting, it's quite the reverse. I admit, I love probability and statistics, and I am something of a closet Bayesian*), but Chivers' light and entertaining style means that what could have been the mathematical equivalent of debating angels on...

Search This Blog