As mentioned in the opening paragraphs of this section, the number of variables is a little high for comfort. When there is a high number of variables the chances of multicollinearity increases. Multicollinearity is when two or more variables are correlated with each other somehow.
From a cursory glance at the data, we can tell that is in fact true. A simple thing to note is GarageArea is correlated with GarageCars. In real life, this makes sense—a garage that can take two cars would be logically larger in area compared to a garage that can only store one car. Likewise, zoning is highly correlated with the neighborhood.
A good way to think about the variables is in terms of information included in the variables. Sometimes, ...
