The probability distribution expressed in Equation (1.30) or Equation (1.50) is ubiquitous in nature and considered Gaussian. It is not surprising then that stochastic diffusion and Gaussian stochastic processes go hand in hand. Since Equation (1.30) represents the probability density of a single variable m, the Gaussian nature is attributed merely to a single point probability ξP t( , )1 in the sense of Equation (2.8).