No. Neither the standard deviation nor the variance can ever be negative.
The mean would be negative, but standard deviation is always positive.
The standard deviation of the population. the standard deviation of the population.
No. It is defined to be the positive square root of ((the sum squared deviation divided by (the number of observations less one))
The standard deviation is 0.
No. Neither the standard deviation nor the variance can ever be negative.
The mean would be negative, but standard deviation is always positive.
No. Standard deviation is the square root of a non-negative number (the variance) and as such has to be at least zero. Please see the related links for a definition of standard deviation and some examples.
A negative Z-Score corresponds to a negative standard deviation, i.e. an observation that is less than the mean, when the standard deviation is normalized so that the standard deviation is zero when the mean is zero.
There is a calculation error.
No. The standard deviation is not exactly a value but rather how far a score deviates from the mean.
no it is not possible because you have to take the square of error that is (x-X)2. the square of any number is always positive----------Improved answer:It is not possible to have a negative standard deviation because:SD (standard deviation) is equal to the square of V (variance).
No, a standard deviation or variance does not have a negative sign. The reason for this is that the deviations from the mean are squared in the formula. Deviations are squared to get rid of signs. In Absolute mean deviation, sum of the deviations is taken ignoring the signs, but there is no justification for doing so. (deviations are not squared here)
Yes. It can have any non-negative value.
The standard deviation is the standard deviation! Its calculation requires no assumption.
The standard deviation of the population. the standard deviation of the population.
No. It is defined to be the positive square root of ((the sum squared deviation divided by (the number of observations less one))