Gaussian Distribution

Gaussian Distribution, also known as Normal Distribution, is a probability distribution that is symmetric around the mean value. It is a continuous probability distribution that is widely used in statistics, probability theory, and data science. The distribution is characterized by two parameters: the mean and the standard deviation. The mean represents the center of the distribution, while the standard deviation represents the spread of the distribution. The probability density function of the Gaussian Distribution is bell-shaped, with the highest point at the mean value and decreasing symmetrically on both sides. The Central Limit Theorem states that the sum of a large number of independent and identically distributed random variables will be approximately normally distributed. This makes the Gaussian Distribution a fundamental concept in statistical inference and hypothesis testing.
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