Gaussiaanse

Gaussiaanse refers to a statistical distribution that is named after the German mathematician Carl Friedrich Gauss. It is also known as the normal distribution or Gaussian distribution. This distribution is characterized by its bell-shaped curve, which is symmetric about the mean. The Gaussian distribution is widely used in statistics and probability theory due to its properties, such as the central limit theorem, which states that the sum of a large number of independent, identically distributed variables tends to be normally distributed, regardless of the original distribution.

The Gaussian distribution is defined by two parameters: the mean (μ) and the standard deviation (σ). The probability density function (PDF) of a Gaussian distribution is given by:

f(x|μ,σ) = (1 / (σ√(2π))) * exp(-(x - μ)² / (2σ²))

where x is a random variable, μ is the mean, σ is the standard deviation, π is the mathematical constant pi, and exp denotes the exponential function.

The Gaussian distribution has several important properties. It is the maximum entropy probability distribution for a given mean and variance, meaning it is the most "random" or "unpredictable" distribution with those constraints. It is also the distribution that results from the sum of a large number of independent, identically distributed random variables, a property known as the central limit theorem.

In practice, the Gaussian distribution is used in various fields, including physics, engineering, economics, and social sciences, to model phenomena that are influenced by a large number of independent factors. Examples include the distribution of heights in a population, measurement errors, and stock price returns.