The normal distribution is a statistical distribution.
Many naturally occurring variables follow the normal distribution: examples are peoples' height, weights.
The sum of independent, identically distributed variables - whatever their own underlying distribution - will tend towards the normal distribution as the number in the sum increases. This means that the mean of repeated measures of ANY variable will approach the normal distribution.
Furthermore, some distributions that are not normal to start with, can be converted to normality through simple transformations of the variable.
These characteristics make the normal distribution very important in statistics. See attached link for more.
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The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.
The domain of the normal distribution is infinite.
It means distribution is flater then [than] a normal distribution and if kurtosis is positive[,] then it means that distribution is sharper then [than] a normal distribution. Normal (bell shape) distribution has zero kurtosis.
No. Normal distribution is a special case of distribution.
The normal distribution can have any real number as mean and any positive number as variance. The mean of the standard normal distribution is 0 and its variance is 1.