The term “probability distribution” relates to probability theory and statistics, offering either 1) the probability of the values of a random variable, assuming that the variable is discrete, or 2) the probability that a value will fall within the parameters of a specific interval, assuming the variable is continuous. Essentially, a probability distribution can be shown with a table or an equation that will connect each outcome from a statistical experiment with the actual probability of that outcome occurring.
The idea behind probability distribution, as well as the random variables which are described by this distribution, is the foundation of a mathematical discipline called probability theory, as well as the entire spectrum of statistical sciences. There is variability and distribution within almost anything that could be measured in a population. For example the sales growth of a company or companies, the height of people, the pliability of a metal, the amount of points scored in a sporting contest, etc. are all definable through this method.
There are a number of probability distributions that tend to come about in a variety of separate situations. Probably one of the most important probability distributions is known as the normal distribution, which may also be called the Gaussian distribution or the bell curve. This tends to estimate a variety of regularly occurring distributions.
Probability distribution places values along normal distribution, which can be demonstrated by a standard curve known as the “bell curve.” The vast majority of statistical experiments will fall within three “standard deviations” from the mean.