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 model information by using the summary function.

Getting ready

You need to have completed the previous recipe by fitting the house rental data into a regression model, and have the fitted model assigned to the variable lmfit.

How to do it…

Perform the following steps to summarize the linear regression model:

1. Compute a detailed summary of the fitted model, lmfit:

   > summary(lmfit)
   Call:
   lm(formula = Price ~ Sqft, data = house)
   
   Residuals:
      Min     1Q Median     3Q    Max
   -76819 -12388  -3093  10024 112227
   
   Coefficients:
               Estimate Std. Error t value Pr(>|t|)
   (Intercept) 3425.133   1766.646   1.939    0.053 .
   Sqft          38.334      1.034  37.090   <2e-16 ***
   Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
   
   Residual standard error...