Carl Tashian in Free Code Camp:
“As an instrument for selecting at random, I have found nothing superior to dice,” wrote statistician Francis Galton in an 1890 issue of Nature. “When they are shaken and tossed in a basket, they hurtle so variously against one another and against the ribs of the basket-work that they tumble wildly about, and their positions at the outset afford no perceptible clue to what they will be even after a single good shake and toss.”
How can we generate a uniform sequence of random numbers? The randomness so beautifully and abundantly generated by nature has not always been easy to extract and quantify. The oldest known dice (4-sided) were discovered in a 24th century B.C. tomb in the Middle East. More recently, around 1100 B.C. in China, turtle shells were heated with a poker until they cracked at random, and a fortune teller would interpret the cracks. Centuries after that, I Ching hexagrams for fortunetelling were generated with 49 yarrow stalks laid out on a table and divided several times, with results similar to performing coin tosses.
But by the mid-1940s, the modern world demanded a lot more random numbers than dice or yarrow stalks could offer. RAND Corporation created a machine that would generate numbers using a random pulse generator. They ran it for a while and gathered the results into a book titled A Million Random Digits with 100,000 Normal Deviates. What now might seem like an absurd art project was, back then, a breakthrough. For the first time, a nice long sequence of high-quality random numbers was made available to the public. The book was reprinted by RAND in 2001 and is available on Amazon.