Parsimony is a 'less is better' concept of frugality, economy, stinginess or caution in arriving at a hypothesis or course of action. The word derives from Middle English parcimony, from Latin parsimonia, from parsus, past participle of parcere: to spare. It is a general principle that has applications from science to philosophy and all related fields. Parsimony is basically the implementation of Occam's razor.

Science

Parsimony is one of the two pillars of science, the first pillar being falsification through experiment, the other taking the results and explaining it with the simplest theory with the best predictive power. See also scientific method.

In science, parsimony is preference for the least complex explanation for an observation. This is generally regarded as good when judging hypotheses. Occam's razor also states the "principle of parsimony".

In systematics, maximum parsimony is a cladistic "optimality criterion" based on the principle of parsimony. Under maximum parsimony, the preferred phylogenetic tree is the tree that requires the smallest number of evolutionary changes.

In biogeography, parsimony is used to infer ancient migrations of species or populations by observing the geographic distribution and relationships of existing organisms. Given the phylogenetic tree, ancestral migrations are inferred to be those that require the minimum amount of total movement.

Parsimony is also a factor in statistics: in general, mathematical models with the smallest number of parameters are preferred as each parameter introduced into the model adds some uncertainty to it. Additionally, adding too many parameters leads to "connect-the-dots" curve-fitting which has little predictive power. In general terms, it may be said that applied statisticians (such as process control engineers) value parsimony quite highly.

Lee and others provide cases where a parsimonious approach does not guarantee to arrive at a correct conclusion, and if based on incorrect working hypotheses or interpretations of incomplete data may even strongly support a false conclusion:

When parsimony ceases to be a guideline and is instead elevated to an ex cathedra pronouncement, parsimony analysis ceases to be science.

For another example using a more familiar subject, consider the attempts to determine the relationships of the cockatoos, namely such taxa as the Gang-gang Cockatoo, the Galah, and the popular pet, the cockatiel. It becomes obvious that parsimony is an extremely powerful tool if the researcher is able to interpret correctly the significance of the data to the case in question, and is able to relate and put it into context inter se. Failure to fulfil these conditions will, speaking figuratively, dull Occam's razor fairly quickly.

Penal ethics

In penal theory and the philosophy of punishment, parsimony refers specifically to taking care in the distribution of punishment in order to avoid excessive punishment. In the utilitarian approach to the philosophy of punishment, Jeremy Bentham's "parsimony principle" states that any punishment greater than is required to achieve its end is unjust. The concept is related but not identical to the legal concept of proportionality. Parsimony is a key consideration of the modern restorative justice, and is a component of utilitarian approaches to punishment, as well as the prison abolition movement. Bentham believed that true parsimony would require punishment to be individualised to take account of the sensibility of the individual – an individual more sensitive to punishment should be given a proportionately lesser one, since otherwise needless pain would be inflicted. Later utilitarian writers have tended to abandon this idea, in large part due to the impracticality of determining each alleged criminal's relative sensitivity to specific punishments.

See also

• Occam's razor
• Maximum parsimony
• Cladistics
• KISS principle
• Karl Popper
• Willi Hennig

References

External links

• Economic Parsimony in Practice at Pinchtown.com
• Essay about parsimony in philosophy and science
• A short blog entry about statistical parsimony