The most common test of statistical significance originated from the Guinness brewery. Here’s how it works
The Guinness brewery has been known for innovative methods ever since founder Arthur Guinness signed a 9,000-year lease in Dublin for £45 a year. For example, a mathematician-turned-brewer invented a chemical technique there after four years of tinkering that gives the brewery’s namesake stout its velvety head. The method, which involves adding nitrogen gas to kegs and to little balls inside cans of Guinness, led to today’s hugely popular “nitro” brews for beer and coffee.
But the most influential innovation to come out of the brewery by far has nothing to do with beer. It was the birthplace of the t-test, one of the most important statistical techniques in all of science. When scientists declare their findings “statistically significant,” they very often use a t-test to make that determination. How does this work, and why did it originate in beer brewing, of all places?
Near the start of the 20th century, Guinness had been in operation for almost 150 years and towered over its competitors as the world’s largest brewery. Until then, quality control on its products consisted of rough eyeballing and smell tests. But the demands of global expansion motivated Guinness leaders to revamp their approach to target consistency and industrial-grade rigor. The company hired a team of brainiacs and gave them latitude to pursue research questions in service of the perfect brew. The brewery became a hub of experimentation to answer an array of questions: Where do the best barley varieties grow? What is the ideal saccharine level in malt extract? How much did the latest ad campaign increase sales?
