Normal distribution is a kind of distribution discovered by Gauss when studying errors. If the random variable X obeys the normal distribution with a mathematical expectation of μ and a variance of σ 2, it is recorded as N(μ, σ 2). The expected value μ of probability density function with normal distribution determines its position, and its standard deviation σ determines its distribution amplitude. When μ=0 and σ= 1, the normal distribution is standard normal distribution.
Graphic feature
Concentration: The peak of the normal curve is located in the center, that is, where the average value is located.
Symmetry: The normal curve is centered on the mean value, which is symmetrical left and right, and both ends of the curve never intersect with the horizontal axis.
Uniform variation: the normal curve starts from the place where the mean value is located and gradually decreases evenly to the left and right sides respectively.
The area between the curve and the horizontal axis is always equal to 1, and the probability of the function equivalent to the probability density function integrating from positive infinity to negative infinity is 1. That is, the sum of frequencies is 100%.
Regarding μ symmetry, the maximum value is taken at μ, the value is taken at positive (negative) infinity, there is an inflection point at μ σ, and the shape is high in the middle and low on both sides. The probability density function curve of normal distribution is bell-shaped, so people often call it bell-shaped curve.