No.
The total deviation from the mean for ANY distribution is always zero.
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"
If the mean is less than or equal to zero, it means there has been a serious calculation error. If the mean is greater than zero and the distribution is Gaussian (standard normal), it means that there is an 84.1% chance that the value of a randomly variable will be positive.
Z score of 0 is the mean of the distribution.
0 (zero).
The mean of a standard normal distribution is 0.
Zero.
The standard normal distribution is a special case normal distribution, which has a mean of zero and a standard deviation of one.
A standard normal distribution has a mean of zero and a standard deviation of 1. A normal distribution can have any real number as a mean and the standard deviation must be greater than zero.
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.
The total deviation from the mean for ANY distribution is always zero.
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 is a subset of a normal distribution. It has the properties of mean equal to zero and a standard deviation equal to one. There is only one standard normal distribution and no others so it could be considered the "perfect" one.
The data from a normal distribution are symmetric about its mean, not about zero. There is, therefore nothing strange about all the values being negative.
The sum of the differences between each score in a distribution and the mean of those scores is always zero because the mean is defined as the balance point of the distribution. When you subtract the mean from each score, the positive differences (scores above the mean) exactly cancel out the negative differences (scores below the mean). This property ensures that the total deviation from the mean is zero, reinforcing the concept that the mean represents the central tendency of the data.
In a normal distribution, the mean and variance are not inherently equal; they are independent parameters. The mean indicates the center of the distribution, while the variance measures the spread or dispersion of the data. However, in a specific case where the mean is set to zero (0) and the variance is set to one (1), they can be equal in value, but this is not a general characteristic of all normal distributions.
The probability of the mean plus or minus 1.96 standard deviations is 0. The probability that a continuous distribution takes any particular value is always zero. The probability between the mean plus or minus 1.96 standard deviations is 0.95