Limiting factor and Probability: Difference between pages

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''Cost and management accounting''.
The study of chance providing an objective measure of uncertainty.


A limiting factor is an input resource which is scarce.


Also known as a ''scarce resource'' or ''key factor''.
Probabilities range between 1 (=100%) and 0 (=0%).


A probability of 100% means that an event is considered certain to occur.


In different simple situations the most important limiting factor may be skilled labour, a physical resource, time, or something else.
A probability of 0% means that an event is considered certain not to occur.


In practice there may well be multiple limiting factors.


For example, flipping an unbiased coin, the probability of getting a head is often modelled as 50%.


In a simple case with a single limiting factor, total contribution and total profit are maximised by focusing on the production that produces the greatest contribution per unit of the limiting factor.
 
This simple model of a coin flip assumes that the only two possibilities are a head or a tail.  Applying such simple models to financial situations, and treating financial outcomes as simple coin flips, may lead to errors resulting from:
 
#The coin landing on its edge 'more often than it's supposed to'.
#The underlying assumption of an unbiased coin not being a valid one. This kind of assumption is usually much too simple.




== See also ==
== See also ==
* [[Contribution]]
* [[Black swan]]
* [[Contribution analysis]]
* [[Conditional probability]]
* [[Factors of production]]
* [[Confidence interval]]
* [[Production possibility curves]]
* [[Frequency distribution]]
* [[Scarcity]]
* [[Mutually exclusive]]
 
* [[Poisson distribution]]
[[Category:The_business_context]]

Revision as of 15:19, 8 June 2016

The study of chance providing an objective measure of uncertainty.


Probabilities range between 1 (=100%) and 0 (=0%).

A probability of 100% means that an event is considered certain to occur.

A probability of 0% means that an event is considered certain not to occur.


For example, flipping an unbiased coin, the probability of getting a head is often modelled as 50%.


This simple model of a coin flip assumes that the only two possibilities are a head or a tail. Applying such simple models to financial situations, and treating financial outcomes as simple coin flips, may lead to errors resulting from:

  1. The coin landing on its edge 'more often than it's supposed to'.
  2. The underlying assumption of an unbiased coin not being a valid one. This kind of assumption is usually much too simple.


See also