The principal should interpret the strength of the association as a strong negative linear relationship between the number of tests students have each week and the amount of time they study for each test. Here's why: 1. The line of fit: The line of fit is a line that best represents the data on a scatter plot. In this case, the line of fit is decreasing, which indicates a negative relationship between the number of weekly tests and the study time per test. 2. The residuals: Residuals are the vertical distances from the actual data points to the line of fit. In this case, the residuals are relatively small, which indicates that the line of fit accurately represents the data. 3. The direction of the association: As the number of weekly tests increases, the study time per test decreases. This is a negative association. 4. The strength of the association: The strength of the association is determined by how closely the data points cluster around the line of fit. In this case, the data points are relatively close to the line of fit, indicating a strong association. Therefore, the principal can conclude that as the number of weekly tests for students increases, the time students spend studying on each test tends to decrease significantly. This is a strong negative linear relationship