 The simplest and most widely-used model for analysing random drift is known as the Wright-Fisher model. This model deals with a finite population containing \(N\) diploid organisms. \(N\) is assumed constant over generations (perhaps because of ecological constraints). Generations are non-overlapping, meaning that parents die as soon as they have reproduced, and mating is random. Selection, migration and mutation are assumed absent. The offspring generation is formed by randomly sampling \(2N\) of the gametes produced by the parental generation. Time is discrete, with one generation corresponding to one time period. Consider a particular allele of interest. Let \(X(t)\) denote the number of copies of the allele in the population in generation \(t\), where \(0 \leq X(t) \leq 2N\) (since organisms are diploid). The allele’s frequency \(p(t)\) is then equal to \(\frac{1}{2N}X(t),\) where \(0 \leq p(t) \leq 1\).