Three stages of statistical development can be recognized in sedimentology. The first is descriptive statistics, in which the sample is the object of interest, and the second is analytical statistics, in which the population assumes major importance. A very large variety of statistical techniques is available for estimating mean values, degrees of variability, tests of differences among population means, linear relations (correlations) among the variables, and ways of evaluating areal variations (trends) in sedimentary phenomena.
The third stage of statistical development is the application of stochastic process models to sedimentology, in which the objective is to discern the probabilistic elements in sedimentary processes, in part by simulation with the high-speed computer. Stochastic process models thus provide one way of examining sedimentary processes through time or over an area. In conjunction with deterministic models they provide a framework for exploring the underlying physical, chemical, and biological controls on sedimentary processes and deposits, with superimposed random fluctuations introduced by the “built–in” probabilistic mechanism.