Click to see additional instructions Consider the following regression results: Call : Im(formula = y ~ x, data = d) Residuals : Min 10 Median 3Q Max -4. 5914 -1. 5431 0. 1266 1.2272 6. 1995 Coefficients : Estimate Std. Error t value Pr(> It|) (Intercept) -0. 1104 0. 2299 -0. 480 0. 632 X -0. 8337 0. 2039 -4. 088 9.74e-05 Residual standard error: 2.14 on 86 degrees of freedom Multiple R-squared: 0.1627, Adjusted R-squared: 0. 153 F-statistic: 16.71 on 1 and 86 DF, p-value: 9. 741e-05 The SSR (Regression Sums of Squares) for this model is (Round your answers to one decimal place).