Lila Knudsen Randolph

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Lila Knudsen Randolph
Born1908
DiedAugust 29, 1965 (aged 56–57)
NationalityAmerican
Alma materUniversity of Minnesota
Scientific career
FieldsStatistics
InstitutionsFood and Drug Administration

Lila Knudsen Randolph (1908[1] – August 29, 1965 in Bethesda, Maryland) was the chief statistician at the Food and Drug Administration[2] and a Fellow of the American Statistical Association.[3] At the FDA, her work involved statistical sampling of food and drugs, and "she was instrumental in developing practical applications of statistics in the validation of analytical methods".[2] She also did early work in computational statistics, writing in the Journal of the American Statistical Association in 1942 about the use of punched cards to construct orthogonal polynomials.[4]

Lila F. Knudsen was originally from Minnesota. She completed her undergraduate education at the University of Minnesota, with additional graduate training at the US Department of Agriculture Graduate School, and became chief statistician at the Food and Drug Administration (FDA) in 1939. She married another FDA worker, Josh Randolph, in 1951, and moved to the National Institutes of Health, where she worked on a part-time basis from 1957 to 1959. She returned to the FDA as a consultant in 1962.[2]

The American Statistical Association elected her as a fellow in 1964 "for her application of statistics to pharmacology and pharmacy; and for the establishment and administration of a statistical program in the Food and Drug Administration".[3]

References[edit]

  1. ^ "Knudsen Randolph (1908-1965)". Find A Grave. Retrieved 17 April 2019.
  2. ^ a b c Connor, William S. (October 1965), "In Memoriam", The American Statistician, 19 (4): 45, doi:10.1080/00031305.1965.10479750
  3. ^ a b "New ASA Fellows – 1964", The American Statistician, 19 (1): 36–37, February 1965, doi:10.1080/00031305.1965.10480393, JSTOR 2682318
  4. ^ Knudsen, Lila F. (1942), "A punched card technique to obtain coefficients of orthogonal polynomials", Journal of the American Statistical Association, 37 (220): 496–506, doi:10.1080/01621459.1942.10500651, JSTOR 2279033, MR 0007132