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The probability density function of the normal distribution, first derived by De Moivre and 200 years later by both Gauss and Laplace independently, is often called the bell curve because of its characteristic shape.

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Gaussian-Distribution

Python 3.6 Python 3.7 Python 3.9 PyPI version

The probability density function of the normal distribution, first derived by De Moivre and 200 years later by both Gauss and Laplace independently, is often called the bell curve because of its characteristic shape.

Notes

The probability density for the Gaussian distribution is

Image of Gaussian Distribution

where μ is the mean and σ the standard deviation. The square of the standard deviation,σ^2 , is called the variance.

The function has its peak at the mean, and its “spread” increases with the standard deviation. This implies that normal is more likely to return samples lying close to the mean, rather than those far away.

Installation

Run the following command in your terminal to install the package:

pip install gaussian-distribution==1.0

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The probability density function of the normal distribution, first derived by De Moivre and 200 years later by both Gauss and Laplace independently, is often called the bell curve because of its characteristic shape.

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