Summarizing multiple regression

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 using the summary function.

Getting ready

You need to have completed the previous recipe by computing the linear model of the income, prestige and women variables from the Prestige dataset, and have the fitted model assigned to the model variable.

How to do it...

Perform the following step to summarize linear model fits:

1. Compute a detailed summary of the fitted model:

        > summary(model)
        Output:
        Call:
        lm(formula = income ~ prestige + women)
        Residuals:
        Min 1Q Median 3Q Max 
        -7620.9 -1008.7 -240.4 873.1 14180.0
        Coefficients:
         Estimate Std. Error t value Pr(>|t|) 
        (Intercept) 431.574 807.630 0.534 0.594 
        prestige 165.875 14.988 11.067 < 2e-16 ***
   ...