How Many Licks? – Aaron Santos ****

Author Aaron Santos takes on the rarely considered but entertaining job of solving Fermi problems: making back-of-an-envelope estimates of numbers that range from the trivial, like the number of licks need to reach the centre of the lolly in the title of the book, to questions like ‘How many babies are born every day?’ The full title is ‘How many licks, or how to estimate damn near anything.’

I thought this might prove a bit samey after a while – there are 69 problems in all, ending in estimating which uses more silicon in the USA, computer chips or silicone implants (I know silicone isn’t the same as silicon, but it does contain it). In fact, each time I wanted to turn on and get to the next one.

The more enthusiastic may want to try to work out some of these as they go along. I was happy to take Santos’ word for it and just enjoy the ride. I do occasionally do this sort of thing for real, but I didn’t particularly want to do so for the problems cited here.

If there’s any complaint it was a slight inconsistency in deciding whether or not to make the assumption that ‘the United States of America’ and ‘the world’ are the same thing (this is, if assumed, not a great piece of estimating on the author’s part). So, for instance, when answering ‘How much deforestation would result each year if people chopped down their (Christmas) trees from a forest rather than getting an artificial tree or getting one from a tree farm?’ the question appears to apply to the whole world, but Santos bases his estimate of ‘How many people get real Christmas trees each year?’ on a percentage of the US population.

That apart, it was fun all the way. The book appears to have been professionally published, though it does rather have the feel of a self-published volume – it’s a little flimsy and unusual in the layout – but seems to have been properly edited and the illustrations and formulae are neatly done.

All in all an enjoyable gift book, or some light reading if you like the idea of playing around with estimating… or just want to be surprised how relatively easy it is estimate some surprisingly obscure numbers.

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Review by Brian Clegg

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