Occam's Razor: one should not increase, beyond what is necessary,
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
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.
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.