In probability theory, the central limit theorem states that, under appropriate conditions, the distribution of a normalized version of the sample mean converges to a standard normal distribution. Thi
This figure demonstrates the central limit theorem. The sample means are generated using a random number generator, which draws numbers between 0 and 100 from a uniform probability distribution. It illustrates that increasing sample sizes result in the 500 measured sample means being more closely distributed about the population mean (50 in this case). It also compares the observed distributions with the distributions that would be expected for a normalized Gaussian distribution, and shows the
Alan Mathison Turing was an English mathematician, computer scientist, logician, cryptanalyst, philosopher and theoretical biologist. He was highly influential in the development of theoretical comput
Central limit theorem
…setting. A curious footnote to the history of the Central Limit Theorem is that a proof of a result similar to the 1922 Lindeberg CLT was the subject of Alan Turing's 1934 Fellowship Dissertation for King's College at the University of Cambridge. Only after submitting the work did Turing learn it had already been…
English Heritage blue plaque in Maida Vale, London, marking Turing's birthplace in 1912
Turing at age 16, c. 1928 – c. 1929
Turing (seated second from left) in Cornwall, with fellow Shirburnians: Edwin Davis, John Bennett, Peter White, Peter Hogg (seated second from right), and Duncan Carse, in April 1930.