The coefficient of determination ($R^2$) is calculated as: $R^2 = \frac{\text{Regression Sum of Squares}}{\text{Total Sum of Squares}}$ Total Sum of Squares = Regression SS + Residual SS = 35.4 + 14.6 = 50.0 $R^2 = \frac{35.4}{50.0} = 0.708$

In a simple linear regression, the correlation coefficient ($r$) is the square root of $R^2$. Its sign is the same as the sign of the slope coefficient. Since the slope is positive (1.2), the correlation coefficient is positive. $r = \sqrt{0.708} = 0.8414 \approx 0.841$