The statistical analysis of accident data has
historically relied on the mathematical precepts of
classical discrete distribution theory Since the first test
of the standard null ("pure chance") hypothesis on accident
mortality data, relating to horsekicks in ten Prussian Army
Corps during 18751894 (von Bortkiewicz, 1898), various
models have been advanced to explain departure from
Poisson's (1837) law.
The ostensibly separate hypotheses of "proneness"
(termed "unequal liability" Greenwood and Yule (1920) and
"false contagion" by others Bates, et al , (1952), and
"contagion" have received extensive attention in the
literature (Newbold, 1927, Anscombe, 1950, Bliss and Fisher,
1953, Neyman, 1939, Cresswell and Froggatt, 1963, Kemp and
Kemp, 1965 and Kemp, 19670). However, despite considerable
development of the associated statistical models, formidable
problems of interpretation remain (Froggatt, 1968a).
