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Scientific American is running an opinion piece that claims the origin of the t-test is a scientist working at the Guinness Brewery in the early 1900s, https://www.scientificamerican.com/article/how-the-guinness-brewery-invented-the-most-important-statistical-method-in/ [scientificamerican.com]

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 had 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?

Amid the flurry of scientific energy, the team faced a persistent problem: interpreting its data in the face of small sample sizes. One challenge the brewers confronted involves hop flowers, essential ingredients in Guinness that impart a bitter flavor and act as a natural preservative. To assess the quality of hops, brewers measured the plants’ soft resin content. Let’s say they deemed 8 percent a good and typical value. Testing every flower in the crop wasn’t economically viable, however. So they did what any good scientist would do and tested random samples of flowers.

The fine article goes on to illustrate the difference between the t-test and normal distribution and also explains why it's often called the "Student" test.

I wonder if it rubs off--can you drink some Guinness Stout and then pass your stat class final exam?

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