Q: What is the difference between a normal distribution and the standard normal distribution?

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standard normal is for a lot of data, a t distribution is more appropriate for smaller samples, extrapolating to a larger set.

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 normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.

when you doesnt have information about the real mean of a population and use the estimation of mean instead of the real mean , usually you use t distribution instead of normal distribution. * * * * * Intersting but nothing to do with the question! If a random variable X is distributed Normally with mean m and standard deviation s, then Z = (X-m)/s has a standard Normal distribution. Z has mean 0 and standard deviation = 1 (or Variance = sd2 = 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.

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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.

standard normal is for a lot of data, a t distribution is more appropriate for smaller samples, extrapolating to a larger set.

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.

A normal distribution is defined by two parameters: the mean, m, and the variance s2, (or standard deviation, s).The standard normal distribution is the special case of the normal distribution in which m = 0 and s = 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"

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.

0.368 or 36.8%.And you should specify that it is a standard normal distribution.0.368 or 36.8%.And you should specify that it is a standard normal distribution.0.368 or 36.8%.And you should specify that it is a standard normal distribution.0.368 or 36.8%.And you should specify that it is a standard normal distribution.

the t distributions take into account the variability of the sample standard deviations. I think that it is now common to use the t distribution when the population standard deviation is unknown, regardless of the sample size.

The standard normal distribution has a mean of 0 and a standard deviation of 1.

The normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.

when you doesnt have information about the real mean of a population and use the estimation of mean instead of the real mean , usually you use t distribution instead of normal distribution. * * * * * Intersting but nothing to do with the question! If a random variable X is distributed Normally with mean m and standard deviation s, then Z = (X-m)/s has a standard Normal distribution. Z has mean 0 and standard deviation = 1 (or Variance = sd2 = 1).

The standard deviation in a standard normal distribution is 1.