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A large standard deviation means that the data were spread out. It is relative whether or not you consider a standard deviation to be "large" or not, but a larger standard deviation always means that the data is more spread out than a smaller one.
For example, if the mean was 60, and the standard deviation was 1, then this is a small standard deviation. The data is not spread out and a score of 74 or 43 would be highly unlikely, almost impossible. However, if the mean was 60 and the standard deviation was 20, then this would be a large standard deviation. The data is spread out more and a score of 74 or 43 wouldn't be odd or unusual at all.
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What does a large standard deviation tell us?
It means that the data are spread out around their central value.
What does a large standard deviation of the equilibrium constant mean?
It means that equilibrium may be attained at widely separated values.
Why variance is bigger than standard deviation?
The variance is standard deviation squared, or, in other terms, the standard deviation is the square root of the variance. In many cases, this means that the variance is bigger than the standard deviation - but not always, it depends on the specific values.
How is standard deviation different from mean absolute decation?
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.
Can standard deviation be calculated for non normal data?
Standard deviation can be calculated using non-normal data, but isn't advised. You'll get abnormal results as the data isn't properly sorted, and the standard deviation will have a large window of accuracy.
