This browser is not much use when it comes to mathematics but I'll try.
Suppose X is a random variable with a Normal distribution and let f(x) be the probability density function of x.
Then the mean is mu = E(X) = Integral of x*f(x) dx over the domain of X [which is negative infinity to positive infinity].
The variance is E{[X - E(X)]2} = Integral of (x - mu)2*f(x) dx over the domain of X.
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 special case of the normal distribution. The standard normal has mean 0 and variance 1.
Z is a variable with mean 0 and variance 1.Z is a variable with mean 0 and variance 1.Z is a variable with mean 0 and variance 1.Z is a variable with mean 0 and variance 1.
It is a discrete distribution in which the men and variance have the same value.
The Normal distribution is a probability distribution of the exponential family. It is a symmetric distribution which is defined by just two parameters: its mean and variance (or standard deviation. It is one of the most commonly occurring distributions for continuous variables. Also, under suitable conditions, other distributions can be approximated by the Normal. Unfortunately, these approximations are often used even if the required conditions are not met!
A normal distribution can have any value for its mean and any positive value for its variance. A standard normal distribution has mean 0 and variance 1.
le standard normal distribution is a normal distribution who has mean 0 and variance 1
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.
Actually the normal distribution is the sub form of Gaussian distribution.Gaussian distribution have 2 parameters, mean and variance.When there is zero mean and unit variance the Gaussian distribution becomes normal other wise it is pronounced as Gaussian.Wrong! The standard normal distribution has mean 0 and variance 1, but a normal distribution is the same as the Gaussiand, and can have any mean and variance. Google stackexcange "what-is-the-difference-between-a-normal-and-a-gaussian-distribution"
The standard normal distribution has mean 0 and variance 1. It is not clear what 0.62 has to do with the distribution.
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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.
The standard normal distribution or the Gaussian distribution with mean 0 and variance 1.
The mean and standard deviation.
The mean is 0 and the variance is 1. This need not be the case in any other Normal (Gaussian) distribution.