What is the method called that calculates worth based on the difference between target values and the average of those values?

The method that calculates worth based on the difference between target values and the average of those values is known as variance. Variance measures the dispersion of a set of values, specifically how far each number in the set is from the mean (average) and thus from every other number in the set. In this context, it helps assess the variability of target values, providing insight into how much the values are spread out from the average.

When applying this concept, the focus is on determining how the individual target values differ from the average value, which is crucial in many statistical analyses, including regression and other predictive modeling scenarios. Understanding variance is essential because it allows analysts to gauge the consistency of data points and can influence decisions in model selection and evaluation.

Entropy and Gini Index are measures of impurity or heterogeneity, commonly used in classification tasks, while an assessment measure generally refers to various methods to evaluate model performance. None of these relate specifically to the calculation involving the average and the differences from it like variance does.