Linear Regression Analysis =========================================================================== Table: Linear Regression Coefficients Estimate Std. Error t value Pr(>|t|) --------------------- --------- ----------- -------- --------- (Intercept) 4.075 0.374 10.893 <.001 anes2020gss.SCICONF -0.949 0.11 -8.664 <.001 anes2020gss.GOPHVOTE 0.9 0.154 5.833 <.001 Table: Regression Residuals Min. 1st Qu. Median 3rd Qu. Max. ------- -------- ------- -------- ------ -3.026 -1.128 -1.027 0.923 4.872 Additional Information: Residual standard error: 1.568 on 1091 degrees of freedom N: 1094 (70 observations deleted due to missingness) Multiple R-squared: 0.167, Adjusted R-squared: 0.166 F-statistic: 109.4 on 2 and 1091 DF, p-value: <.001 Dependent variable: anes2020gss$V202336xR Observations weighted by: anes2020gss$V200017b Answer this question with the linear regression provided above: Dario was concerned that since Republicans are also often skeptical of the scientific community, that the two variables may be multicollinear. What sentence best characterizes how to address Dario's concerns? Multicollinearity is a concern because the coefficients are both just under the absolute value of one. Multicollinearity is a concern because the R-squared indicates most of the variation is still unexplained. Doesn't have that much impact on the variable, not related to multicolinearity Multicollinearity is not a concern in the model because both variables are significant. Multicollinearity is not a concern in the model because