Perform the following step to summarize linear model fits:

1. Compute a detailed summary of the fitted model:

        > summary(lmfit)
        Output:
        Call:
        lm(formula = y1 ~ x)

        Residuals:
             Min 1Q Median 3Q Max 
        -1.92127 -0.45577 -0.04136 0.70941 1.83882 

        Coefficients:
                    Estimate Std. Error t value Pr(>|t|) 
        (Intercept) 3.0001 1.1247 2.667 0.02573 * 
        Quartet$x 0.5001 0.1179 4.241 0.00217 **
        ---
        Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

        Residual standard error: 1.237 on 9 degrees of freedom
        Multiple R-squared: 0.6665, Adjusted R-squared: 0.6295 
        F-statistic: 17.99 on 1 and 9 DF, p-value: 0.00217