Though early sociologists had valid concerns about the limitations of the scientific method and whether the method could be applied to questions of behavior, many of the tools they used were and are valid measures of aggregate data. When behavior moves into the realm of one hundred percent predictable, it may be possible to apply the scientific method. Few social scientists can claim one hundred percent accuracy of behavior models, even when behavior appears universal.

For example, the scientific method might hypothesize that a human subject responds to hunger triggers by eating. On the surface, this claim seems self-evident and, likely, the scientific method would discover a high rate of results to prove its accuracy. But the scientific method would also have to call the experiment a failed one due to the "what ifs" the question poses. Social scientists know, however, that there are too many variables in the scenario to hope to find a truth, much less the truth. Social scientists would approach the question hoping to find conditional patterns (if, then), aggregate data (number of solutions out of number of respondents), and predictive models (when this happens, that happens).

Relying on observable, aggregate data to discover and/or explain principles of behavior may never be as conclusive as the scientific method. There will always be exceptions to the rule. Yet, less than one hundred percent accuracy does not render a conclusion useless. If seventy, eighty, or ninety percent of human subjects respond to hunger triggers by eating, the results are consistent enough to consider them predictive and still leave room for exceptions.