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.
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.
Perform the following step to summarize linear model fits:
- 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 *** ...