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!
The standard normal distribution is a special case of the normal distribution. The standard normal has mean 0 and variance 1.
In a normal distribution half (50%) of the distribution falls below (to the left of) the mean.
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 distribution of the sample mean is bell-shaped or is a normal distribution.
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.
le standard normal distribution is a normal distribution who has mean 0 and variance 1
The mean of a standard normal distribution is 0.
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.
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.
In a normal distribution half (50%) of the distribution falls below (to the left of) the mean.
The standard normal distribution has a mean of 0 and a standard deviation of 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 normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 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"
In the normal distribution, the mean and median coincide, and 50% of the data are below the mean.
The distribution of the sample mean is bell-shaped or is a normal distribution.