Occam's Razor: one should not increase, beyond what is necessary,
the number of entities required to explain anything.


Occam's razor is one tool we use in choosing among differing facts or explanations, e.g., dates for the birth of a Bucklin, or the occurrence of events.

Occam's razor is a logical principle attributed to the mediaeval philosopher William of Occam (or Ockham).  He stated in writing a principle that since time out of memory has been used by philosophers.  William just happened to state it in writing in mediaeval times and so got his name associated with the principle.  (It also is known as the philosophical principle of parsimony, but that is a little too alliterative to sound scholarly.)

The Occam's razor principle is that one should not make more assumptions than the minimum needed to explain something.  The principal  underlies  good scientific theory building. In other words: choose from a set of otherwise equivalent models of a given phenomenon the simplest one. In any given explanation of reality,  Occam's razor helps us to "shave off" those concepts, variables or constructs that are not really needed to explain the phenomenon. By doing that, in developing the theory that explains reality, there is less chance of introducing inconsistencies, ambiguities and redundancies.

For a given set of data, there is always an infinite number of possible models explaining those same data. This is because a theoretical model normally represents an infinite number of possible cases, of which the observed cases are only a finite subset. The more complicated the theoretical model of reality, the more extensive becomes the data that has to be explained by the model. observations.

Geometry will help us given an example of the need for Occam's razor. For example, if you see two data points, you can induce that all other data will lie on that line, or you can induce that the data lie on a three dimensional  structure of unknown size.  Both theories of reality explain the two data points. Only Occam's razor would in this case guide you in choosing the "straight" (i.e. linear) relation as best candidate model.  Using the linear relation may be wrong, but it will help you find more data more reliably that trying to find all possible other data.

 If one starts with too complicated foundations for a theory that potentially encompasses the universe, the chances of getting any manageable model are very slim indeed. Moreover, the Occam's razor principle is sometimes the only remaining guideline when no concrete tests or observations can decide between rival models.

Generally (not always), we here at the Joseph Bucklin Society, in our forensic reconstruction of history, induce that model which fits the known facts and minimizes the number of additional assumptions.