Stochastic Models in Medicine and Biology

Proceedings of a Symposium conducted by the Mathematics Research Center, United States Army, at the University of Wisconsin, Madison, June 12–14, 1963, edited by John Gurland, Mathematics Research Center, U.S. Army, University of Wisconsin. xvi + 393 pages, illustrated. The University of Wisconsin Press, Madison. 1964. $6.00

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  • Division of Biostatistics Tulane University School of Medicine, New Orleans, Louisiana

In many fields of scientific endeavor a careful scrutiny of the situation being investigated may suggest a formalized analytic structure or, as it is usually referred to, a mathematical model, for the description of the given system. To a degree, depending on the complexity of the problem, a model may be thought of as an idealized image constructed upon directly or indirectly observed elements of the system and a set of assumptions encompassing all of its pertinent aspects. A model may be purely deterministic or probabilistic, or it may involve both deterministic and probabilistic elements. Briefly, a deterministic model may be said to lead to a unique prediction of the state of a given system, whereas a probabilistic (or stochastic) model incorporates chance fluctuations of the system and consequently allows for a prediction in terms of a probability statement. Experience indicates that the problem of constructing a plausible model for a biological system or for a population consisting of biological organisms is quite complex.