Statistical modeling is the next step up from simple hypothesis tests; it involves a larger number of explanatory variables, a larger number of levels within each explanatory variable, or both. At this stage we are still only concerned with one response variable.
Models are fit to test the importance of different variables in relation to the response variable, to predict future outcomes, and to assign uncertainty and repeatability to the results.
For example, you may want to test if a variable has a significant effect on an outcome, or you could test ...
