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.
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.
The standard normal distribution is a normal distribution with mean 0 and variance 1.
The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.
le standard normal distribution is a normal distribution who has mean 0 and variance 1
When its probability distribution the standard normal distribution.
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No, the normal distribution is strictly unimodal.
The domain of the normal distribution is infinite.
Yes. When we refer to the normal distribution, we are referring to a probability distribution. When we specify the equation of a continuous distribution, such as the normal distribution, we refer to the equation as a probability density function.
The standard normal distribution has a mean of 0 and a standard deviation of 1.
The Normal distribution is, by definition, symmetric. There is no other kind of Normal distribution, so the adjective is not used.
The normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.
A mathematical definition of a standard normal distribution is given in the related link. A standard normal distribution is a normal distribution with a mean of 0 and a variance of 1.