It is any standardised distribution.
standard normal
The answer depends on the degrees of freedom (df). If the df > 1 then the mean is 0, and the standard deviation, for df > 2, is sqrt[df/(df - 2)].
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.
Z-scores standardize data from various distributions by transforming individual data points into a common scale based on their mean and standard deviation. This process involves subtracting the mean from each data point and dividing by the standard deviation, resulting in a distribution with a mean of 0 and a standard deviation of 1. This transformation enables comparisons across different datasets by converting them to the standard normal distribution, facilitating statistical analysis and interpretation.
When the normal curve is plotted using standard deviation units, each with a value of 1.00, it is referred to as the standard normal distribution. In this distribution, the mean is 0 and the standard deviation is 1, allowing for easy comparison of different data sets by transforming them into z-scores. The standard normal distribution is often represented by the symbol Z.
Mean 0, standard deviation 1.
No.
The standard normal distribution has a mean of 0 and a standard deviation of 1.
standard normal
The normal distribution would be a standard normal distribution if it had a mean of 0 and standard deviation of 1.
a is true.
idk about normal distribution but for Mean "M" = (overall sum of "x") / "n" frequency distribution: 'M' = Overall sum of (' x ' * ' f ') / overall sum of ( ' f ' ) M = Mean x = Mid Point f = frequiency n = number of variables ALL FOR STANDARD DEVIATION * * * * * A general Normal distribution is usually described in terms of its parameters, and given as N(mu, sigma2) where mu is the mean and sigma is the standard deviation. The STANDARD Normal distribution is the N(0, 1) distribution, that is, it has mean = 0 and variance (or standard deviation) = 1.
It is called a standard normal distribution.
The answer depends on the degrees of freedom (df). If the df > 1 then the mean is 0, and the standard deviation, for df > 2, is sqrt[df/(df - 2)].
Mean = 0 Standard Deviation = 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).
probability is 43.3%