Faced with an apparent pattern in any data, a key question is always: “Does this pattern represent something real, or is it just chance?” The simplest example: if I measure the heights of five men and five women and discover that the men tend to be taller than the women, I might be on to something, or I might just have some tall men and some short women in my sample. Based on this small sample, how confident should I be that men are in general taller than women?

The statistical apparatus to check this is a test called Student's t-test. Student was the pseudonym of William Sealy Gosset, an amiable, rucksack-wearing chemist who – beginning in 1899 – worked all his adult life for Guinness and eventually rose to the rank of head brewer. So nervous was the company about commercial confidentiality that Gosset published surreptitiously under his pseudonym.

From the outset, Gosset's focus was practical – as the economist and historian Steve Ziliak has discovered through his work in the Guinness archives. To produce beer to a high standard on an industrial scale, Gosset needed to sample and experiment with hops, malt and barley. But experiments are expensive and Gosset developed his small-sample methods because he wanted to understand how many experiments were necessary to be confident of his results. That was a clear trade-off: how much confidence is “enough” depends on the costs of further research and the benefits of extra precision.