What distinguishes multiple linear regression from multiple bivariate correlations (like you would see in a correlation matrix) for the same variables? O There is no limit to the number of bivariate correlations you can test, while the number of relationships tested in multiple linear regression is limited by Type I error proobability. O In multiple linear regression, the predictor variables are not confounded with each other, as they are in multiple bivariate correlations. O In multiple linear regression, you can have multiple outcome variables, while there is only one outcome variable in bivariate correlation. Bivariate correlation allows you to determine statistical signficance, while multiple linear regression is not a null hypothesis test