standard normal
It depends on what the distribution is. In a Normal or Gaussian distribution, the standard deviation is the square root of the mean, so it could be 3.1 but, again, it depends on the distribution.
The mean deviation (also called the mean absolute deviation) is the mean of the absolute deviations of a set of data about the data's mean. The standard deviation sigma of a probability distribution is defined as the square root of the variance sigma^2,
The statement is probably: The mean and standard deviation of a distribution are 55 and 4.33 respectively.
It is any standardised distribution.
with mean of and standard deviation of 1.
Mean 0, standard deviation 1.
Standard deviation describes the spread of a distribution around its mean.
It depends on what the distribution is. In a Normal or Gaussian distribution, the standard deviation is the square root of the mean, so it could be 3.1 but, again, it depends on the distribution.
The standard normal distribution has a mean of 0 and a standard deviation of 1.
The mean deviation (also called the mean absolute deviation) is the mean of the absolute deviations of a set of data about the data's mean. The standard deviation sigma of a probability distribution is defined as the square root of the variance sigma^2,
The statement is probably: The mean and standard deviation of a distribution are 55 and 4.33 respectively.
No.
The mean and standard deviation often go together because they both describe different but complementary things about a distribution of data. The mean can tell you where the center of the distribution is and the standard deviation can tell you how much the data is spread around the mean.
It is any standardised distribution.
If repeated samples are taken from a population, then they will not have the same mean each time. The mean itself will have some distribution. This will have the same mean as the population mean and the standard deviation of this statistic is the standard deviation of the mean.
The mean and standard deviation.
with mean of and standard deviation of 1.