I am working on a paper where the methodology was already approved. I know it isn't the "best" way to analyze my question but I am moving forward with it.

Essentially, I am analyzing whether increasing school funding mitigates the impact of poverty on student performance. I am doing this using three variables - 1) Student Assessment Scores, 2) Percentage of Students Receiving Free or Reduced Lunch, 3) Expenditures Per Student.

When I run the multiple regression, I get Unstandardized Betas that are .000 for Expenditures Per Student and -.*** for Free or Reduced Lunch. The Standardized Betas are -.*** for Expenditures Per Student (ie: -.131, -.119, -.150) and -.*** for Free or Reduced Lunch (ie: -.780, -.752, -.473).

In addition, I do have the results of the simple regressions for just student performance and Free or Reduced Lunch with which I could compare the slopes.

I am thinking that this shows that increasing expenditures does not have much of an impact.

Is it right that I can compare the Unstandardized Beta from the simple regression with the Unstandardized Beta from the multiple regression and if the Beta is larger (closer to zero or positive) in the multiple regression it would indicate that increased funding mitigated the impact but if it doesn't change funding wouldn't matter?

How would I determine if this is significant or not?