Normal distribution, also known as Gaussian distribution, is a probability distribution that is often used in statistics to model continuous random variables that are naturally occurring in the real world. The shape of the normal distribution is bell-shaped and symmetrical, with most of the observations clustering around the mean, and the probabilities of observations decreasing as one moves further away from the mean.
The normal distribution is characterized by two parameters: the mean, which represents the center of the distribution, and the standard deviation, which represents the spread of the distribution. The mean is denoted by the Greek letter mu (μ), and the standard deviation is denoted by the Greek letter sigma (σ).
Many natural phenomena such as the height and weight of people, test scores, and errors in measurements follow a normal distribution. The normal distribution is also important in statistical inference as many statistical methods rely on the assumption that the data are normally distributed.
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