PROBABILITY DISTRIBUTION

    The probability is the chance that something will happen; according to Rouse is a science that allows calculating the likelihood of a given event is occurrence (Rouse, 2005), coinciding
with Doane and Seward, who explain to us that the probability of an event is a number that measure the relative likelihood that the event will occur; it is denoted with P, must be between 0
to 1. We can collect the information to get the probability from three different ways: Empirical, Classical, and Subjective. (Doane & Seward, 2011).
    A probability distribution is considering a rule according to which probability is apportioned, or distributed, among the different sets in the sample space, it just list every element in the sample and allots it a probability between 0 and 1. (The University of Auckland, 2011).
    Binomial probability distribution summarizes the number of observations, when each observation has the same probability of attaining one particular value (Investopedia ULC), this model originates from the repetition of Bernoulli experiment, where each trial is independent and the probability of success stays constant for each trial (Doane & Seward, 2011). The binomial process is useful to resolve many problems e.g. how many of health insurance holders will claim in a given period, how many deficient medication from a production line, or how many people have any specific opinion about any specific situation.
    Poisson distribution probability is a statistical distribution that show us the frequency probability of specific event when the average probability of a single occurrence is known (Investopedia ULC) , it describe the number of occurrences within a randomly chose unit of time or space, the events must occur randomly and independently over a continuum of time or space (Doane & Seward, 2011).
    It statistics distribution has application in many science like medicine; we can get a probability of cardiac malformation at birth, or a number of death from Diabetes Mellitus.
    Normal probability distribution, also known as a Gaussian distribution, is defined by the mean and standard deviation (Doane & Seward, 2011), it plot all of its value a symmetrical fashion and most of the result are situated around the probability of mean (Investopedia ULC).
    We can apply a normal probability distribution if we known de mean and standard deviation of any study sample.

Bibliography
Doane, D. P., & Seward, L. E. (2011). Applied Statistics in Business & Economics. New York: McGraw-Hill
Irwin.
Investopedia ULC. (n.d.). investopedia.com. Retrieved July 1, 2012, from
http://www.investopedia.com/terms/b/binomialdistribution.asp
Rouse, M. (2005, Dec). Whatls.com the leading IT encyclopedia and learning center. Retrieved July 1,
2012, from TeachTarget: http://whatis.techtarget.com/definition/