# Variance of indivudial variables in multiple regression

#### anarchyrose

##### New Member
Greetings, I am doing a linear multiple regression model in spss.
this being the model: CB = β0 + β1SCC + β2D + ε.
I have the values for β0, β1, β2, but how can I see the amount of variance explained by the each variable? do I just run the model without the second variable and look at R2?
also how can I see if the variables combined explain more variance than them separetly,

kindest regards

#### spunky

##### Doesn't actually exist
I have the values for β0, β1, β2, but how can I see the amount of variance explained by the each variable?
To answer this kind of questions you'd need to use methods related to variable importance in OLS multiple regression like Dominance Analysis or the Pratt Index. Here's a good overview of these methods:

https://onlinelibrary.wiley.com/doi/pdf/10.1002/wics.1346

Depending on which software you're using, people have developed packages or macros that can do these calculations. I use R and the R package taht does this is called relaimpo.

#### noetsi

##### Fortran must die
I can't get access to that article spunky. But in any case is explained variance the same as the impact of an x on Y (relative to another x)? I would think this would be tied to change in Y given an X (standardized slope) not explained variance. But maybe they are the same thing....