Answer:
b.
Step-by-step explanation:
standard deviation measures the degree of dispersion of a dataset relative to its mean and is calculated as the square root of the variance, which determines each data point's deviation relative to the mean.
in other words, for each data point is difference to the mean value is calculated and squared (so, this is always positive, no matter if the data point is larger or smaller than the mean). all these squared differences are added, and then the standard deviation is the positive square root of that sum.
it is the same, if all the data points are dispersed in the same way below the mean or above.
therefore, the standard deviation is always positive. in an extreme case it can be 0 (all data points have the same value), but it cannot be negative. it would not make any sense to use the negative square root in the calculation mentioned above.
therefore, b. is the right answer.