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Distribution.
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.

Trials
Number of times the experiment is repeated is called as number of trials.

Binomial Distribution.
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.

Poisson Distribution.
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.