Dirichlet Distributions

(I included this graphical representation of the K parameters because I thought the data set looked really nifty when graphed.  Plus it is much more impressive than my description!)

"In probability and statistics, the Dirichlet distribution is a family of continuous multivariate probability distributions parametrized by a vector of positive real numbers". (Wikipedia) The idea of the Dirichlet distribution is based upon the work of the seminal mathematician Johann Peter Gustav Lejeune Dirichlet who was known not only for having a ridiculously long name but also for his brilliant advances in number theory.  "The Dirichlet distribution is commonly used in Bayesian statistical analysis as a prior probability function to determine an integer for an uncertain quantity."  The prior probability function could be used to represent, for example, the number of likely voters in an upcoming election.  With this being said the Dirichlet distribution is a continuous sample of positive real numbers which could potentially be represented in a data set. (Wikipedia)