040. Probability Distributions

A Random variable is a variable whose value is the result of a random event. Number of units sold, daily levels of output, and the height of customers are Examples.

A Probability distribution is a display of all possible outcomes of an experiment along with the probabilities of each outcome. Probability distributions are based on the outcomes of random variables. There are several different Types of probability distributions:

· Binomial distributions.

· Poisson distributions.

· Hypergeometric distributions.

· Uniform distributions.

· Exponential distributions.

· Normal distribution.

The probability that the random variable X can take on some specific value, Xi is written

P(X = Xi).

It should be noted that

0 ≤ P(X = Xi) ≤ 1 and ΣP(X = Xi) = 1.

The use of a discrete random variable leads to the formation of a Discrete probability distribution. The number of customers, the number of units sold are Examples.

The use of continuous random variable leads to formation of a Continuous probability distribution. A continuous probability distribution is usually the result of measurement. There are no gaps in the observations because no matter how close two observations might be, a third could be found that would fall between the first two.

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