It is a discrete probability distribution that is used to model real-life events that occur rarely or in situations where the probability of an event occurring is proportional to the time which has passed....

The posterior probability distribution is a used term in Bayesian analysis. It tells us the distribution of some unspecified parameter after (posterior) the collection of some data has been done. The collected information along...

Suppose we are given some grouped data in tabulated form along with the frequencies. The cumulative frequency means the total of all the frequencies of the current and previous class intervals. The distribution table...

Suppose you are given the joint probability distribution of two variables X and Y. Then the marginal probability distribution is the distribution of one of the variables alone without consideration to the other variable....

Suppose we have a sample of 100 people with half of them male and half of them female. Let us assume that a person has either black or blue eyes. We might be interested...

A joint probability distribution tells us about how two or more random variables are distributed. For example, let X denote the height of a person and Y denote the weight of a person. Here...

Truncated distributions are those distributions for which some of the domain values have been cut off as they cannot be realistically attained in some given real-life application.
We need to make changes in the...

A compound probability distribution is the distribution of some combination of independent and identically distributed variables whose parameters themselves follow some probability distribution.
Compound Poisson Distribution:
Suppose X1,…, XN are independent and identically distributed Poisson variables...