Abstract
Abstract This paper studies the Boisson process, precisely the number of arrivals (according to the Boisson distribution) and inter - arrival times (according to the exponential distribution ) and arrival times (according to the gamma distribution) from the point view of bayes statistics which is posterior in information, i.e., using the past experiences which represents the prior distribution, besides the direct data, which represents likelihood function in founding posterior distribution of Boisson process, then estimate the mean and the variance of this distribution, and using it with the classic way in studying the number of patients arriving to the consultative clinic of fracture in al-Salam hospital/Mosul. The researchers concluded that bayes statistics, which is posterior in information, could be used studying stochastic process, especially the Boisson process. .
