In a study examining the relationship between study hours and test scores, a linear regression line was fitted to the data. One student studied for $6$ hours and scored $82$, while the average test score of all students was $75$. Which of the following best describes the explained variation for this student?

The squared distance between the student’s predicted score and their actual score; $(y_i-{\hat{y}}_i{)}^2$

The squared distance between the predicted score and the mean score; $({\hat{y}}_i-\bar{y}{)}^2$

The squared distance between the actual score and the mean score; $(y_i-\bar{y}{)}^2$

The difference between the predicted score and the regression slope.