In statistics, probability distributions are very important measure which related to the random variable and statistical data. Every data patern follows a probability distribution. Continuous data follow the continuous distribution and discrete data follow the discrete distributions. According to wikipedia,
“In probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment. It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events.”
The idea of a probability distribution exactly parallels that of a frequency distribution. Each type of distribution is based on a set of mutually exclusive and exhaustive measurement classes or class intervals. A probability distribution is thus an idealization of the way things might be if we only had all the information. It dictates what we should expect to observe in a frequency distributions, if some given state of affairs is true. Thus, we can say,
Any statement of a function associating each of a set of mutually exclusive and exhaustive classes or class intervals with its probability is called probability distribution.
A probability distribution is divided into two category. They are-
- Discrete probability distribution
- Continuous probability distribution
Discrete Probability Distributions
A discrete random variable assumes each of its values or numbers with a certain probability. A probability distribution with discrete random variable is called discrete probability distribution.