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Distribution gives idea about how individuals are distributed in the population. It can be represented by a generalized frequency curve. The distribution can also be represented by some mathematical relationship known as distribution function.
Number of times the experiment is repeated is called as number of trials.
A random variable has a binomial distribution if it denotes number of successes of a particular event in n number of trials and p is the probability of success in each trial. Probability of success remains same for all trials. Binomial distribution has two parameters (n,p). It is a discrete distribution e.g. number of heads obtained in tossing of a fair coin for n times. Variable representing binomial distribution is a binomial variable or binomial variate. See chapter 4 for more details.
A random variable has a poison distribution if it denotes number of successes of a particular event when x units are picked up from population and m is the mean value of successes e.g Finding probability that sample of 10 units would contain 2 defectives if probability of finding defective is .05. Poisson distribution has only one parameter m. It is a discrete distribution. Poisson distribution is usually applied where probability of success is quite low e.g number of accidents, number defective products etc. Variable representing poisson distribution is a poisson variable or poisson variate. See chapter 4 for more details.