Samuel Stanley Wilks
| Samuel S. Wilks | |
|---|---|
| Born |
June 17, 1906 Little Elm, Texas |
| Died | March 7, 1964 (aged 57) Princeton, New Jersey |
| Nationality | American |
| Fields | Mathematical statistics |
| Institutions | Princeton University |
| Alma mater | University of Iowa |
| Doctoral advisor | Henry Louis Rietz |
| Doctoral students |
Theodore Wilbur Anderson Wilfrid Dixon Ted Harris Donald A. S. Fraser Frederick Mosteller George W. Brown Alexander Mood |
| Known for | Wilks's lambda distribution |
Samuel Stanley Wilks (June 17, 1906 – March 7, 1964) was an American mathematician and academic who played an important role in the development of mathematical statistics, especially in regard to practical applications.
Wilks was born in Little Elm, Texas and raised on a farm. He studied Industrial Arts at the North Texas State Teachers College in Denton, Texas, obtaining his bachelor's degree in 1926. He received his master's degree in mathematics in 1928 from the University of Texas. He obtained his Ph.D. at the University of Iowa under Everett F. Lindquist; his thesis dealt with a problem of statistical measurement in education, and was published in the Journal of Educational Psychology.
Wilks became an instructor in mathematics at Princeton University in 1933; in 1938 he assumed the editorship of the journal Annals of Mathematical Statistics in place of Harry C. Carver. Wilks assembled an advisory board for the journal that included major figures in statistics and probability, among them Ronald Fisher, Jerzy Neyman, and Egon Pearson.
During World War II he was a consultant with the Office of Naval Research. Both during and after the War he had a profound impact on the application of statistical methods to all aspects of military planning.
Wilks was named professor of mathematics and director of the Section of Mathematical Statistics at Princeton in 1944, and became chairman of the Division of Mathematics at the university in 1958.
Wilks died in 1964 in Princeton.
He was noted for his work on multivariate statistics. He also conducted work on unit-weighted regression, proving the idea that under a wide variety of common conditions, almost all sets of weights will yield composites that are very highly correlated (Wilks, 1938), a result that has been dubbed Wilks's theorem (Ree, Carretta, & Earles, 1998).
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