The probability distribution of a discrete random variable is the list of all possible values and the probability of each value occurring. This definition cannot be applied to continuous random variables because the probability of any one outcome is zero (there is an infinite number of outcomes and any finite number divided by infinity is zero). However, it is possible to list the probabilities of ranges of values. For discrete variables the probability distribution is called the probability mass function. For continuous variables, it is called the probability density function.
The knowledge of the theoretical probability distribution is of great use in the understanding and analysis of a large number of business and economic situations. For example, with the use of probability distribution, it is possible to test a hypothesis about a population, to take decision in the face of uncertainty, to make forecast, etc.
Theoretical probability distributions can be divided into two broad categories, viz. discrete and continuous probability distributions, depending upon whether the random variable is discrete or continuous. Although, there are a large number of distributions in each category, we shall discuss only some of them having important business and economic applications.
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Quantitative Techniques – Introduction
Measures Of Central Tendency
Linear Programming: Graphical Method
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Waiting Model (queuing Theory)
Theoretical Probability Distributions
Probability Distribution Of A Random Variable
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