Brief Biography
Frank Proschan was born and raised in the slums of Manhattan, New York. Growing up in a crowded tenement, Proschan developed an interest in probability at an early age by playing dice for pocket change with other children. He attended Townsend Harris High School, the preparatory school for the City College of New York, and chose to further pursue the study of statistics. At CCNY he interacted with future Nobel Prize-winning economist and OR leader Kenneth J. Arrow. After graduating in 1941, Proschan accepted a position as a cement quality specialist with the National Bureau of Standards. He was later employed by the U.S. Geological Survey, making maps by stereoscopic methods. During World War II he worked on classified air-mapping projects in the Pacific Theater. In 1945, W. Edwards Deming helped Proschan land a position with the U.S. Army Security Agency, introducing the young man to early computing systems.
Proschan worked towards a master’s degree by taking night classes at George Washington University in the late 1940s. It was as a GW graduate student teaching five courses that he abandoned the traditional “formula” of mathematics instruction and developed his own style of teaching. using jokes and wisecracks to keep the students engaged. Proschan originally intended to continue on to a PhD but instead accepted a position at Sylvania Electric Products.
After working on theory-driven Sylvania projects for a number of years, Proschan decided to once again try for a PhD. On a fellowship from the National Science Foundation, he enrolled at Stanford University in 1956. At Stanford, Proschan reunited with Deming and Arrow and was introduced to Richard Barlow, a fellow employee of Sylvania’s Electronic Defense Laboratories. In 1965 Proschan and Barlow published The Mathematical Theory of Reliability and, ten years later, its succesor, Statistical Theory of Reliability and Life Testing (1975). These two books were responsible for defining reliability theory. In 1991, the Operations Research Society of America jointly awarded both men the John von Neumann Theory Prize for their contributions to the subject.
When Proschan went back to Sylvania full-time in 1959, he expected a raise in salary, having now received a PhD in Statistics. When the company failed to deliver, he accepted a higher-paying position at Boeing Scientific Research Laboratories (BSRL) in Seattle. Though Proschan was assigned to the specific tasks of quality management and reliability, there was a tremendous level of research freedom. Acting primarily as a researcher, he noticed that the data he collected were often times cited more than his actual analysis or application.
When BSRL lost funding from the United States Air Force, most of the scientists obtained academic positions. Proschan followed this trend and joined the Department of Statistics at Florida State University in 1971. The transition from researcher and consultant to academic was, in his words, “a great shock to a delicate nervous system”. Proschan was most critical of “democratic self-rule”, favoring the corporate model of decision-making where administrative choices, such as the price for a cup of coffee, were left to a single leader rather than by a committee of the whole. Administrative annoyances aside he enjoyed teaching his students, constantly creating new material for them and introducing his classes to whatever subject he was researching at the time.
Prior to his death, Proschan received numerous accolades and honors. In addition to winning the John von Neumann Theory Prize, he is an elected fellow of the American Statistical Association and the Institute for Operations Research and the Management Sciences.
Other Biographies
Education
City College of New York, BS 1941
George Washington University, MS 1948
Stanford University, PhD 1959 (Mathematics Genealogy)
Affiliations
Academic Affiliations
- Stanford University
- The George Washington University
- University of California, Berkeley
- City College of New York
- Florida State University
Non-Academic Affiliations
- Boeing
- Sylvania Electric Products Inc.
- U. S. Army
- National Bureau of Standards
- U.S. Geological Survey
Key Interests in OR/MS
Methodologies
Application Areas
- Biometry
Oral Histories
Hollander M. & Marshall A. W. (1995) A Conversation with Frank Proschan. Statistical Science, 10(1): 118-133. (link)
Obituaries
Hollander M. & Marshall A. W. (1995) A Conversation with Frank Proschan. Statistical Science, 10(1): 118-133. (link)
Hollander M. (2004) Frank Proschan: Obituary. Institute of Mathematical Statistics Bulletin, 33(2): 9.
Awards and Honors
American Statistical Association Fellow 1965
American Statistical Association Samuel S. Wilks Award 1982
John von Neumann Theory Prize 1991
Institute for Operations Research and the Management Sciences Fellow 2002
Selected Publications
Barlow R. E., Marshall A. W. & Proschan, F. (1963) Properties of probability distributions with monotone hazard rate. The Annals of Mathematical Statistics, 34(2): 375-389.
Proschan F. (1963) Theoretical explanation of observed decreasing failure rate. Technometrics, 5(3): 375-383.
Barlow R. E. & Proschan F. (1965) Mathematical Theory of Reliability. John Wiley & Sons: New York.
Esary J. D., Proschan F., & Walkup D. W. (1967) Association of random variables, with applications. The Annals of Mathematical Statistics, 38(5): 1466-1474.
Barlow R. E. & Proschan F. (1975) Statistical Theory of Reliability and Life Testing: Probability Models. Holt, Rinehart and Winston: New York.
Barlow R. E. & Proschan F. (1975) Importance of system components and fault tree events. Stochastic Processes and Their Applications, 3(2): 153-173.
Brown M. & Proschan F. (1983) Imperfect repair. Journal of Applied Probability, 20(4): 851-859.
Joag-Dev K. & Proschan F. (1983) Negative association of random variables with applications. The Annals of Statistics, 11(1): 286-295.
Hollander M. & Proschan F. (1984) The Statistical Exorcist: Dispelling Statistics Anxiety. Marcel Dekker: New York.
Pecaric J. E., Proschan F., & Tong Y. L. (1992) Convex Functions, Partial Orderings, and Statistical Applications. Academic Press: Boston.