I followed this tutorial to learn Hierarchical Linear Regression (HLR) in R, but couldn't understand how to interpret its sample output of >anova(model1,model2,model3)

The tutorial simply says

each predictor added along the way is making an important contribution to the overall model.

But I would like some more details to quantify the contribution of each explanatory variable, like:

1. "UNEM" explains X (or X%) deviance

2. Adding the "HGRAD" variable explains Y (or Y%) more deviance

3. Adding the "INC" variable further explains Z (or Z%) more deviance

So, can I get the value of X, Y, and Z using the above ANOVA table? How? Specifically, what do Res.Df, RSS, Sum of Sq mean in this ANOVA table?

I followed this tutorial to learn Hierarchical Linear Regression (HLR) in R, but couldn't understand how to interpret its sample output of >anova(model1,model2,model3)

The tutorial simply says

each predictor added along the way is making an important contribution to the overall model.

But I would like some more details to quantify the contribution of each explanatory variable, like:

1. "UNEM" explains X (or X%) variance

2. Adding the "HGRAD" variable explains Y (or Y%) more variance

3. Adding the "INC" variable further explains Z (or Z%) more variance

So, can I get the value of X, Y, and Z using the above ANOVA table? How? Specifically, what do Res.Df, RSS, Sum of Sq mean in this ANOVA table?