In order to see how the IVs influence the DV through the variance explained why don't you just look at the ANOVA table which for each variable provides the amount of remaining variance explained by that IV.

In order to see how the IVs influence the DV through the variance explained why don't you just look at the ANOVA table which for each variable provides the amount of remaining variance explained by that IV. In the newly provided ANOVA table in the edited question we see that the sum of squares explained by IV 1 is 1721.6 and 918.6 for IV 2. So in this sense IV 1 has a lot more influence on the DV then IV 2 when both are included in the model. Nevertheless you can see that both have huge values for their respective F statistics indicating that their coefficients are very significant for this model.

Why don't you just look at the ANOVA table which for each variable provides the amount of remaining variance explained by that IV.

In order to see how the IVs influence the DV through the variance explained why don't you just look at the ANOVA table which for each variable provides the amount of remaining variance explained by that IV.