Experiment and analysis show that some of the most primitive examples of random phenomena (tossing a coin, spinning a roulette wheel, and shuffling cards), under usual circumstances, are not so random. The lecture will examine the philosophical basis of randomness and implications for the use (and misuse) of statistical  models. At the age of 14, Persi Diaconis dropped out of school to become an apprentice to Canadian sleight-of-hand expert Dai Vernon. After frequenting casinos and other venues where he perfected his skills in games of chance, he returned to school without a high school diploma intent on learning calculus in order to help him understand the mathematical basis for calculating odds. Graduating from City College of New York at the age of 26, he applied to Harvard’s graduate program in mathematics and statistics. He received his Ph.D. from Harvard in 1974. He started his teaching career at Stanford University in 1974, becoming a professor of statistics in 1981. In 1987 he returned to Harvard to become the G. V. Leverett Professor of Mathematics before moving in 1996 to Cornell, where he was the David Duncan Professor of Mathematics. He has been the Mary Sunseri Professor of Statistics and a professor of mathematics at Stanford since 1998. Diaconis is well known as one of two researchers—David Bayer of Columbia University is the other—who demonstrated in 1992 that the random ordering of a deck of cards requires seven riffle shuffles. Much of his work continues to focus on everyday phenomena of randomness. His Princeton lecture will examine these phenomena and the extent to which they are actually random.