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Because the average deviation will always be zero.
The standard deviation is a measure of how much variation there is in a data set. It can be zero only if all the values are exactly the same - no variation.
A standard deviation of zero means that all the data points are the same value.
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 doesn't matter whether comparisons are involved. A small standard deviation indicates that population values are likely to be clustered closely around the mean.
No. The average of the deviations, or mean deviation, will always be zero. The standard deviation is the average squared deviation which is usually non-zero.
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.
Because the average deviation will always be zero.
Standard deviation shows how much variation there is from the "average" (mean). A low standard deviation indicates that the data points tend to be very close to the mean, whereas high standard deviation indicates that the data are spread out over a large range of values.
The standard deviation must be greater than or equal to zero.
no
Its zero dummy
If the standard deviation of 10 scores is zero, then all scores are the same.
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.
Standard deviation (SD) is a measure of the amount of variation or dispersion in a set of values. It quantifies how spread out the values in a data set are from the mean. A larger standard deviation indicates greater variability, while a smaller standard deviation indicates more consistency.
No. Variance and standard deviation are dependent on, but calculated irrespective of the data. You do, of course, have to have some variation, otherwise, the variance and standard deviation will be zero.
[10, 10, 10, 10, 10, 10, 10] has a mean of 10 and a standard deviation of zero.