The sum of squares of the deviations of observations is minimum when the deviations are taken from:

✅Explanation:
The sum of squares of the deviations of observations is minimum when the deviations are taken from the arithmetic mean. This is because the arithmetic mean represents the "center" of the data set, and any deviation from it will be squared and added, minimizing the overall sum.

• Here's why the other options are incorrect:
● Median: While the median divides the data set into two equal halves, it doesn't necessarily minimize the sum of squared deviations. Deviations from the median can be large for values on either side, leading to a higher sum of squares.
● Standard Deviation: The standard deviation itself represents the average deviation from the mean, not the deviations themselves. It doesn't make sense to take deviations from the standard deviation.
● Geometric Mean: The geometric mean is not commonly used to calculate deviations. It's more relevant for multiplying or comparing ratios of data points.