The Normal Distribution is a statistical model that describes the distribution of a variable in which most observations fall within a certain range, called the “bell curve.” The Normal Distribution is named after mathematician and physicist Abraham de Moivre, who described it in 1734. The Normal Distribution is characterized by its bell-shaped curve, which means that the probability that a given data set will fall within a certain range is unevenly distributed. This means there is a greater chance that some data sets will fall closer to the center of the distribution curve than others.
The bell curve is named after it and resembles the shape of a bell, which is said to be the result of the random distribution of points within a given population.
The Normal Distribution describes various phenomena, including data from random samples, probability distributions, and normal curves. It is used to describe the probability that a given sample will fall within certain ranges, as well as the expected value and variance of the sample. The Normal Distribution describes the probability of success in a given endeavor and the odds of various outcomes.
The Normal Distribution is used in many fields of study, including mathematics, statistics, business, and engineering. For example, the Normal Distribution is a cornerstone of many statistical models and is often used to describe randomly distributed data.
