In the same way that you calculate mean and median that are greater than the standard deviation!
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.
Standard deviation in statistics refers to how much deviation there is from the average or mean value. Sample deviation refers to the data that was collected from a smaller pool than the population.
There is no such thing. The standard error can be calculated for a sample of any size greater than 1.
You need more than one number to calculate a standard deviation, so 9 does not have a standard deviation.
Standard deviation can be greater than the mean.
It does not indicate anything if the mean is greater than the standard deviation.
In general, a mean can be greater or less than the standard deviation.
In the same way that you calculate mean and median that are greater than the standard deviation!
Yes; the standard deviation is the square root of the mean, so it will always be larger.
The standard deviation must be greater than or equal to zero.
Let sigma = standard deviation. Standard error (of the sample mean) = sigma / square root of (n), where n is the sample size. Since you are dividing the standard deviation by a positive number greater than 1, the standard error is always smaller than the standard deviation.
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.
It is the value that is one standard deviation greater than the mean of a Normal (Gaussian) distribution.
No. A small standard deviation with a large mean will yield points further from the mean than a large standard deviation of a small mean. Standard deviation is best thought of as spread or dispersion.
Standard deviation is a measure of the dispersion of the data. When the standard deviation is greater than the mean, a coefficient of variation is greater than one. See: http://en.wikipedia.org/wiki/Coefficient_of_variation If you assume the data is normally distributed, then the lower limit of the interval of the mean +/- one standard deviation (68% confidence interval) will be a negative value. If it is not realistic to have negative values, then the assumption of a normal distribution may be in error and you should consider other distributions. Common distributions with no negative values are gamma, log normal and exponential.
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