The Gaussian distribution function, often referred to as the normal distribution function, is a mathematical function that describes the probability distribution of a continuous random variable. This function is characterized by a bell-shaped curve symmetrically centered around its mean (average) value.
In simpler terms, the Gaussian distribution function provides a way to model the likelihood of different outcomes occurring within a dataset. It is defined by two parameters: the mean, which represents the central tendency, and the standard deviation, which measures the spread of the distribution.
This distribution is widely encountered in various fields, from statistics to physics and finance. It is a fundamental concept in probability theory, providing a robust framework for analyzing and understanding the distribution of random variables in diverse applications.
