Important discrete probability distribution is Poisson exponential distribution, named after Simeon Demis Poisson, a Frenchmen who developed the distribution from studies in 1837. The Poisson distribution is used to describe a number of processes that involves an observation per unit of time or space. The binomial distribution is based on ascertaining the probability of a ‘r’ success in one trial. What then constitute one trial in a Poisson/Distribution? In the case of a batch of parts, an observation of a single part to determine whether it is defective is of a single part to determine whether it is defective, is of course, a trial.
Like binomial distribution, the Poisson distribution has three significant attributes. They are mean, standard division and shape of the distribution.
The Poisson distribution is positively skewed (P being small). Given the value of P, nP, will increase in n. As μ or nP increases, the Poisson distribution will be closer and closer to bell shaped distribution. That is why, normal distribution is also the limit of the Poisson distribution.
To Submit your assignment on Poisson distribution please click the button belowSUBMIT ASSIGNMENT NOW!