John Wilder Tukey (June 16, 1915 - July 26, 2000) was a statistician. Born New Bedford, Massachusetts, Tukey obtained a Master's Degree in chemistry from Brown University before moving to Princeton University in 1937 to study for his doctorate in mathematics.
During World War II, Tukey worked at the Fire Control Research Office and collaborated with Samuel Wilks and William Cochran.
After the war, he returned to Princeton, dividing his time with AT&T Bell Laboratories.
Among many contributions to civil society, Tukey served on a committee of the American Statistical Association that produced a report challenging the conclusions of the Kinsey Report, Statistical Problems of the Kinsey Report on Sexual Behavior in the Human Male.
Retiring in 1985, Tukey died in New Brunswick, New Jersey.
His statistical interests were many and varied. He is particularly remembered for his development, with James Cooley of the Fast Fourier transform algorithm.
He also contributed to statistical practice and articulated the important distinction between exploratory data analysis and confirmatory data analysis, believing that much statistical methodology placed too great an emphasis on the latter. Though he believed in the utility of separating the two types of analysis, he pointed out that sometimes, especially in natural science, this was problematic and termed such situations uncomfortable science.
A D Gordon offered the following summary of Tukey's principles for statistical practice:
... the usefulness and limitation of mathematical statistics; the importance of having methods of statistical analysis that are robust to violations of the assumptions underlying their use; the need to amass experience of the behaviour of specific methods of analysis in order to provide guidance on their use; the importance of allowing the possibility of data's influencing the choice of method by which they are analysed; the need for statisticians to reject the role of 'guardian of proven truth', and to resist attempts to provide once-for-all solutions and tidy over-unifications of the subject; the iterative nature of data analysis; implications of the increasing power, availability and cheapness of computing facilities; the training of statisticians.
