I need help with A Figure 6: The regression outputsDependent Variable: y(Intercept)|Model 1: y = a + Bx₂ + e₁dxEstimate Std. Error t value Er(> [t|)4.23886-0.15714Signif. codes: 0 0.001 0.01 0.05 . 0.1¹ 1Residual standard error: 0.07632 on 298 degrees of freedomMultiple R-squared: 0.05761, Adjusted R-squared:F-statistic: 18.22 on 1 and 298 DF, p-value: 2.65e-050.09726 43.581 <2e-16 ***0.03682 -4.268 2.65e-05● Model 2: Ay+ = a + BAx₂ + eiDependent Variable: dyEstimate Std. Error t value Pr(> |t|](Intercept) -0.0006393 0.0012531 -0.5100.6100.0825935 0.0612668 1.3480.1790.05445Residual standard error: 0.02166 on 297 degrees of freedomMultiple R-squared: 0.006082, Adjusted R-squared: 0.002735F-statistic: 1.817 on 1 and 297 DF, P-value: 0.1787(a) Write the sample regression function(i.e., predicted y and predicted Ay) for bothModel 1 and Model 2.

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X ● Dependent Variable: y (Intercept) 1 Figure 6: The regression outputs dx Model 1: y = a + Bx₂ + e₁ ● Signif. codes: 0 0.001 0.01 Residual standard error: 0.07632 on 298 degrees of freedom Multiple R-squared: 0.05761, Adjusted R-squared: F-statistic: 18.22 on 1 and 298 DF, p-value: 2.65e-05 0.05445 Estimate Std. Error t value Er(>1t|) 4.23886 -0.15714 0.09726 43.581 <2e-16 *** -4.268 2.65e-05 ** 0.03682 Model 2: Aye = a + BAx₂ + ei 0.05 ¹.0.1 1 Dependent Variable: dy Estimate Std. Error t value Pr (>|t|| (Intercept) -0.0006393 0.0012531 -0.510 0.0825935 0.0612668 1.348 0.610 0.179 Residual standard error: 0.02166 on 297 degrees of freedom Multiple R-squared: 0.006082, Adjusted R-squared: F-statistic: 1.817 on 1 and 297 DF, p-value: 0.1787 0.002735 (a) Write the sample regression function(i.e., predicted y and predicted Ay) for both Model 1 and Model 2.

X ● Dependent Variable: y (Intercept) 1 Figure 6: The regression outputs dx Model 1: y = a + Bx₂ + e₁ ● Signif. codes: 0 0.001 0.01 Residual standard error: 0.07632 on 298 degrees of freedom Multiple R-squared: 0.05761, Adjusted R-squared: F-statistic: 18.22 on 1 and 298 DF, p-value: 2.65e-05 0.05445 Estimate Std. Error t value Er(>1t|) 4.23886 -0.15714 0.09726 43.581 <2e-16 * -4.268 2.65e-05 0.03682 Model 2: Aye = a + BAx₂ + ei 0.05 ¹.0.1 1 Dependent Variable: dy Estimate Std. Error t value Pr (>|t|| (Intercept) -0.0006393 0.0012531 -0.510 0.0825935 0.0612668 1.348 0.610 0.179 Residual standard error: 0.02166 on 297 degrees of freedom Multiple R-squared: 0.006082, Adjusted R-squared: F-statistic: 1.817 on 1 and 297 DF, p-value: 0.1787 0.002735 (a) Write the sample regression function(i.e., predicted y and predicted Ay) for both Model 1 and Model 2.

College Algebra

7th Edition

ISBN:9781305115545

Author:James Stewart, Lothar Redlin, Saleem Watson

Publisher:James Stewart, Lothar Redlin, Saleem Watson

Chapter1: Equations And Graphs

Section: Chapter Questions

Problem 10T: Olympic Pole Vault The graph in Figure 7 indicates that in recent years the winning Olympic men’s...

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