What is calculated by squaring the differences in target values in a subset?

The calculation that involves squaring the differences in target values within a subset refers to the process of determining variance. Variance measures how far a set of numbers (in this case, target values) are spread out from their mean. It is computed by taking the average of the squared differences between each target value and the overall mean of the target values in the subset.

The concept of variance is crucial in statistics as it provides insight into the dispersion of data points, indicating how much the data points differ from the mean. Therefore, the correct answer highlights the significance of variance in statistical analysis.

The other options relate to different statistical measures or concepts. Worth typically refers to the value assigned to something rather than a measure of dispersion. Entropy is a concept from information theory that quantifies uncertainty or disorder in a dataset, while the Gini Index measures statistical dispersion and inequality within a distribution. Each of these concepts serves a unique purpose, but they do not involve the specific calculation of squaring differences around a mean in the same way that variance does.