Answer:
Postive, The coefficient of determination is a measure of how well the regression line fits the data points. It represents the proportion of variation in the dependent variable that can be explained by the independent variable. The coefficient of determination ranges from 0 to 1, with higher values indicating a stronger relationship between the variables. Importantly, it cannot be negative.
The coefficient of determination is equal to the square of the coefficient of correlation, which measures the strength and direction of the linear relationship between two variables. However, unlike the coefficient of determination, the coefficient of correlation can be negative or positive. A negative value indicates an inverse relationship between the variables, while a positive value indicates a direct relationship.
The coefficient of determination, also known as R-squared, is a measure of how well the regression line fits the data. It represents the proportion of variation in the dependent variable that can be explained by the independent variable(s). R-squared ranges from 0 to 1, with higher values indicating a better fit. It cannot be negative, as it is a squared value. The square root of the coefficient of correlation is equal to the coefficient of determination. The coefficient of correlation can be negative or positive, indicating the direction of the relationship between the variables.