When its probability distribution the standard normal distribution.
I apologize my question should have read what are the characteristics of a standard normal probability distribution? Thank you
a mean of 1 and any standard deviation
The mean must be 0 and the variance must be 1.
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When its probability distribution the standard normal distribution.
I apologize my question should have read what are the characteristics of a standard normal probability distribution? Thank you
with mean and standard deviation . Once standardized, , the test statistic follows Standard Normal Probability Distribution.
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.
with mean of and standard deviation of 1.
Normal distribution is the continuous probability distribution defined by the probability density function. While the binomial distribution is discrete.
Zero.
It is the Standard Normal distribution.
The normal distribution and the t-distribution are both symmetric bell-shaped continuous probability distribution functions. The t-distribution has heavier tails: the probability of observations further from the mean is greater than for the normal distribution. There are other differences in terms of when it is appropriate to use them. Finally, the standard normal distribution is a special case of a normal distribution such that the mean is 0 and the standard deviation is 1.
a mean of 1 and any standard deviation
The mean must be 0 and the variance must be 1.
I have included two links. A normal random variable is a random variable whose associated probability distribution is the normal probability distribution. By definition, a random variable has to have an associated distribution. The normal distribution (probability density function) is defined by a mathematical formula with a mean and standard deviation as parameters. The normal distribution is ofter called a bell-shaped curve, because of its symmetrical shape. It is not the only symmetrical distribution. The two links should provide more information beyond this simple definition.