What are some strengths and weaknesses of quantitative research?

Quantitative research is a fantastic tool for expanding human understanding.  By using the time-honored tenets of scientific inquiry, it pushes back the dark curtains of ignorance in our lives.  It is “systematic and purposeful.”  It “is conducted and reported in such a way that the argument can be examined painstakingly.  The report does not depend for its appeal on the eloquence of the writer or any surface plausibility.” It usually “assumes there are stable, social facts with a single reality, separated from the feelings and beliefs of individuals.” In quantitative research, “there is an established set of procedures and steps that guide the researcher.”  The researcher must remain “detached from the study to avoid bias.”  By doing all these things, quantitative research sheds informational light on the subject under study, allowing improved predictability and suggesting how changes in process could result in changes in outcomes.  It specific, practical, and observable.  By “observable,” I mean that the process by which a conclusion is reached and the facts upon which that conclusion is made are exposed to the reader and subject to independent scrutiny.  The conclusions can be judged in the context of the process, the facts, the methodology, and the solidity of the statistical outcomes.  It can also be replicated, checked against differing situations, places, people, and times for verification of universality.  It is an incredibly powerful tool to refine and improve outcomes.

The famous quote “there are lies, damn lies, and statistics” captures the flavor of the weakness of quantitative research.  It is possible to design studies such that essential causal factors are missed.  It is very easy to confuse correlation for causation in such studies (though after many years of use, I would like to think this is not such an easy mistake to sell anymore).  It is not hard to “data mine” samples for facts which support the desired argument while ignoring facts which do not. Finally, there are subjects, which are inaccessible to statistical methods, or are anyway better portrayed in a holistic representation of the words and experiences of the participants.  I think Mark Twain compared humor to dissecting frogs, claiming “both suffer from the experience.”  Likewise, many aspects of human existence lose a great measure of “truth” when broken into constituent parts.  Certainly, it takes a particular sensitivity to run the wheels of the quantitative research machine along the grain of life such that the reductionist techniques leave the reality of life intact.