Simple linear and multiple regressions are tools that we use to identify the predictive power of one or more variables on an outcome (aka dependent variable.) For example, in your agency you may be looking at the performance of your employees (aka dependent variables). A regression would allow you to identify what factors are the most important predictors of the performance of those employees. Or you may want to test the best set of independent variables that predict an outcome, say a set of variables that predicts well-being. We call this a "predictive model."

In this discussion, define the differences between simple linear and multiple regressions. Share a possible topic you are interested in that would require a simple linear regression. How would you convert it into a multiple regression?