One of the most significant continuous theoretical distributions in statistics is the normal probability distribution. The majority of data in the social and physical sciences as well as economics and business statistics follow this distribution.
The normal distribution was initially identified by English mathematician De-Moivre (1667–1744) in 1733. He did this by solving issues that came up in games of chance and obtaining the distribution’s mathematical equation. In honor of Karl Friedrich Gauss (1777–1855), who used this distribution to explain the idea of accidental errors, the normal distribution is sometimes known as the Gaussian distribution (Gaussian Law of Errors). The normal probability model is now one of the most significant models of probability used in statistical analysis.
The below calculator will randomly generate a set of data values following a normal distribution with specified mean and variance.
Mean of dataset: 0.023
Standard deviation of dataset: 0.849