so with the following output from r, how would i answer part a:Call: lm(formula = qsec ~ mpg, data = mtcars) Residuals: Min 1Q Median 3Q Max -2.8161 -1.0287 0.0954 0.8623 4.7149 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 15.35477 1.02978 14.911 2.05e-15 *** mpg 0.12414 0.04916 2.525 0.0171 * --- Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1 Residual standard error: 1.65 on 30 degrees of freedom Multiple R-squared: 0.1753, Adjusted R-squared: 0.1478 F-statistic: 6.377 on 1 and 30 DF, p-value: 0.01708 > newdata <- data.frame(mpg = 17.5) > predict(model, newdata) 1 17.52716