Venn That Tune - Andrew Viner ****

There is something delightful about a book that combines mathematical/graphical notation with the names of pop songs. This unashamed gift book has a series of pages, each illustrating one song title using a diagram. About a half are Venn diagrams with the rest being various forms of chart, some more obscure than others. This is much easier to see than understand from a description. Here’s the diagram that’s on the cover of the book a little more clearly:

The idea is to guess the tune from the diagram (I love this particular example). There are answers in the back, but for one like this you shouldn’t need to check it – it’s like a good crossword clue, when you get the answer, it’s obviously right.

One of the reason this particular one works well is that the song is well-known. With some of the more obscure numbers (for example It’s ‘Orrible Being in Love (When you’re 8½)) it’s not quite such a certain experience, so you are more likely to approximate to the answer than get it spot on, unless you have a passion for obscure song titles.

This is an ideal gift – especially for someone who’s mathematically or musically minded (or even both). I’ll certainly be buying a few. It’s one of those classic ‘books I probably wouldn’t buy myself, but I’d love to be given’ presents. It’s just a shame that it wasn’t available in the US until after Christmas 2008 – it’ll have to be a birthday present instead there.

Of course there are plenty of tunes missing – Andrew Viner admits he ran out of space (I wanted to see ‘Venn you walk all alone, keep your head up high’, which I know technically isn’t the title of the song, but hey) – but those that are there will keep anyone with an enquiring mind and a sense of fun amused and entertained. Recommended.

Hardback:

Using these links earns us commission at no cost to you

Review by Brian Clegg

Comments

David Spiegelhalter Five Way interview

Professor Sir David Spiegelhalter FRS OBE is Emeritus Professor of Statistics in the Centre for Mathematical Sciences at the University of Cambridge. He was previously Chair of the Winton Centre for Risk and Evidence Communication and has presented the BBC4 documentaries Tails you Win: the Science of Chance, the award-winning Climate Change by Numbers. His bestselling book, The Art of Statistics , was published in March 2019. He was knighted in 2014 for services to medical statistics, was President of the Royal Statistical Society (2017-2018), and became a Non-Executive Director of the UK Statistics Authority in 2020. His latest book is The Art of Uncertainty . Why probability? because I have been fascinated by the idea of probability, and what it might be, for over 50 years. Why is the ‘P’ word missing from the title? That's a good question. Partly so as not to make it sound like a technical book, but also because I did not want to give the impression that it was yet another book

Vector - Robyn Arianrhod ****

This is a remarkable book for the right audience (more on that in a moment), but one that's hard to classify. It's part history of science/maths, part popular maths and even has a smidgen of textbook about it, as it has more full-on mathematical content that a typical title for the general public usually has. What Robyn Arianrhod does in painstaking detail is to record the development of the concept of vectors, vector calculus and their big cousin tensors. These are mathematical tools that would become crucial for physics, not to mention more recently, for example, in the more exotic aspects of computing. Let's get the audience thing out of the way. Early on in the book we get a sentence beginning ‘You likely first learned integral calculus by…’ The assumption is very much that the reader already knows the basics of maths at least to A-level (level to start an undergraduate degree in a 'hard' science or maths) and has no problem with practical use of calculus. Altho

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