The square of the standard deviation is called the variance.
Variance measures the spread of a set of numbers. It indicates how much the numbers in a dataset deviate from the mean (average) value. When you took the square root of the variance, you returned to the standard deviation, which provides a more interpretable measure of spread in the same units as the original data. Simply put, while standard deviation gives a sense of how much the data points deviate from the mean in their original scale, variance provides that same insight but on a squared scale, highlighting the extent of variability within the dataset.