What is the squared difference called when subtracting the mean from each number?

When subtracting the mean from each number in a dataset, the squared difference is referred to as the variance. Variance is a statistical measurement that captures how far each number in the set deviates from the mean, on average. By squaring these differences, variance addresses the issue of negative numbers that may arise when values are below the mean, ensuring that all deviations contribute positively to the total measurement of dispersion.

This calculation allows for an assessment of the distribution of data points around the mean, providing critical insight into the variability within the dataset. A higher variance indicates that the numbers are spread out over a wider range, while a lower variance signifies that they are closer to the mean. In contrast, standard deviation is simply the square root of the variance, which translates the variance back into the same unit of measurement as the original data, making it more interpretable. The other choices do not pertain to the operation of subtracting the mean from each number in this context.