Standard deviation can be greater than the mean.
Yes. If the variance is less than 1, the standard deviation will be greater that the variance. For example, if the variance is 0.5, the standard deviation is sqrt(0.5) or 0.707.
If I have understood the question correctly, despite your challenging spelling, the standard deviation is the square root of the average of the squared deviations while the mean absolute deviation is the average of the deviation. One consequence of this difference is that a large deviation affects the standard deviation more than it affects the mean absolute deviation.
What is mean deviation and why is quartile deviation better than mean deviation?
Prob(X > 0.57) = Prob(Z > 2) = 0.02275 = 2.275%
There's no valid answer to your question. The problem is a standard deviation can be close to zero, but there is no upper limit. So, I can make a statement that if my standard deviation is much smaller than my mean, this indicates a low standard deviation. This is somewhat subjective. But I can't make say that if my standard deviation is many times the mean value, that would be considered high. It depends on the problem at hand.
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.
Yes, the mean deviation is typically less than or equal to the standard deviation for a given dataset. The mean deviation measures the average absolute deviations from the mean, while the standard deviation takes into account the squared deviations, which can amplify the effect of outliers. Consequently, the standard deviation is usually greater than or equal to the mean deviation, but they can be equal in certain cases, such as when all data points are identical.
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.
Yes, the coefficient of variation (CV) can be greater than 100%. The CV is calculated as the ratio of the standard deviation to the mean, expressed as a percentage. If the standard deviation is greater than the mean, which can occur in certain datasets, the CV will exceed 100%, indicating high relative variability compared to the average value.
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.
It is the value that is one standard deviation greater than the mean of a Normal (Gaussian) distribution.
Yes - but the distribution is not a normal distribution - this can happen with a distribution that has a very long tail.