Testing homoscedasticity for multiple regression in SPSS I am conducting a multiple regression with 1 DV and 6 IVs. I am trying to test Homoscedasticity on SPSS using a scatterplot since all my variables are scales. I conducted a the residual vs predictor value scatterplot and I think it might be a little heteroscadestic. 
How do I know which variable is the one causing the problem? And what should the next step be to try to make my data homoscedastic? 
 A: In regression analysis, residuals should be independent from response variable, all of the predictors as well as the predicted value of response variable. You can detect, if there is any pattern in these plots in SPSS using these steps: 
Analyze > Regression > linear > plots [Zresidual vs Zpredicted and zresidual vs dependent]. It is also better to plot Zresidual Vs all predictors.
Now if the assumption of homoscedasticity is violated, then you can use regression with WLS weights. To compute weights in SPSS: 
Analyze > Regression > weight estimation > select dependent & independent variables (SPSS use these names for response and predictors) > select weight variable for which hetroscedasticity is detected. The default power range is -2 to 2 by 0.5 in SPSS.> Click Ok > read the power for which log likelihood is maximize
Repeat the test few more time by narrowing the range with smaller increment to get better weight and save variable by using options in weight estimation.
Rerun regression using these weight.
