Summarizing linear model fits

The summary function can be used to obtain the formatted coefficient, standard errors, degree of freedom, and other summarized information of a fitted model. This recipe introduces how to obtain overall information on a model through the use of the summary function.

Getting ready

You need to have completed the previous recipe by computing the linear model of the x and y1 variables from the quartet, and have the fitted model assigned to the lmfit variable.

How to do it...

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 **
        ---
    ...