Suppose you have a very simple linear model to predict Salary. Your ridiculously simple model is based on a persons age and their education level which can have the values: None, High School, College, Post Grad.
gm0 <- lm( Salary ~ Age+EducationLevel, data=dfWork ) summary(gm0)
Now you run the summary. The coefficient for Age turns out to be so significant that p is almost zero. As for education level the results are mixed. The only value with a significant p is EducationLevel=College.
So ... umm ... what do you do with this information? Do you include EducationLevel in the model even though only one of the values is significant? Do you scrap it because only one value is significant? Or do you make a new column with a value=1 when EducationLevel=College, 0 otherwise and include THAT categorical variable into the model (and not the original EducationLevel).