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)].
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 statement is probably: The mean and standard deviation of a distribution are 55 and 4.33 respectively.
It is any standardised distribution.
standard normal
with mean of and standard deviation of 1.
Mean 0, standard deviation 1.
The mean of a distribution gives no information about the standard deviation.
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.
No.
The statement is probably: The mean and standard deviation of a distribution are 55 and 4.33 respectively.
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.
The mean and standard deviation.
NO
Standard deviation and variance