Reaction to "A Brief History of the Hypothesis"

            One of my earliest recollections of science courses from elementary school is of being introduced to the term “hypothesis.”  At this age, it was simply defined as an educated guess, and we were told a hypothesis is imperative to conduct scientific studies.  My classmates and I then proceeded to carry out a rudimentary experiment observing a caterpillar undergo a metamorphosis to a butterfly.  It is still a commonly held belief amongst most of society that, for an experiment to be of any merit, it must contain a hypothesis. However, as Glass and Hall (2008) explain in their article about the history of the term hypothesis, a significant amount of research today takes place without a well-defined hypothesis.  Rather, the studies are primarily driven by inductive reasoning that aims to answer questions that the researchers have.  While this method has its shortcomings, I find it to be the most practical way to practice in the future as a physician.

            A central argument that some philosophers put forth against inductive reasoning is the idea that we cannot predict future events (Glass & Hall, 2008).  It is true that humans cannot be absolutely sure that something will occur in the future.  However, it would be foolish to view happenings as stand-alone events that have no connection to the past or future.  We are handcuffed by the unknown, but we must act as though events will occur in a similar manner in the future.  A practical application of this belief is a physician treating a patient with a disease in the same way as he or she treated a patient with the same disease in the past.  One should stay open to the idea that the future may stray from the past, and make the appropriate adaptations if this occurs.

            As was mentioned by Glass and Hall (2008) and discussed in depth in class, probability helps defend inductive reasoning.  Still, there exists the chance of any event occurring in the future.  A statistical principle known as the Law of Large Numbers states that, as the number of experiments held increases, we become closer to obtaining the true probability of that event occurring.  Therefore, the probability of an event can essentially be taken as zero if it has not happened after countless tests.

            Other fields of study may be different, but formulating a concrete hypothesis often does not apply to biology.  As one of the students mentioned during discussion, there are usually a tremendous amount of variables present to account for in biological research.  One must resort to observing a system repeatedly and try to make general conclusions that try to explain the results.  This is a great example of inductive reasoning in action.

            An interesting claim that the article makes is that hypotheses are not relevant today due partially to the abundance of information we have accumulated.  Instead of formulating hypotheses to try to falsify, the authors suggest that researchers search for solid answers to questions.  My brief research experience has been based around the latter of these two options.  In fact, it would be foreign for me to try and function under the premise of the first option.  Trying to answers may not be the absolute method to conduct scientific research, but it will likely remain as the primary school of thought in the foreseeable future.

Literature Cited:

Glass, D. J. & Hall, N.  (2008).  A Brief History of the Hypothesis.  Cell, 134, 378-381.