Probability: Difference between revisions
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imported>Doug Williamson (Link with Confidence interval page.) |
imported>Doug Williamson (Classify page.) |
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The study of chance providing an objective measure of uncertainty. | The study of chance providing an objective measure of uncertainty. | ||
Probabilities range between 1 (=100%) and 0 (=0%). | |||
Probabilities range between 1 (= 100%) and 0 (= 0%). | |||
A probability of 100% means that an event is considered certain to occur. | A probability of 100% means that an event is considered certain to occur. | ||
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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 problem=== | ||
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 | #The coin landing on its edge 'more often than it's supposed to'. | ||
#The underlying assumption of an unbiased coin not being valid. | #The underlying assumption of an unbiased coin not being a valid one. This kind of assumption is usually much too simple. | ||
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* [[Confidence interval]] | * [[Confidence interval]] | ||
* [[Frequency distribution]] | * [[Frequency distribution]] | ||
* [[Mutually exclusive]] | |||
* [[Poisson distribution]] | * [[Poisson distribution]] | ||
[[Category:The_business_context]] | |||
[[Category:Identify_and_assess_risks]] | |||
[[Category:Manage_risks]] | |||
[[Category:Risk_frameworks]] | |||
[[Category:Risk_reporting]] |
Latest revision as of 16:59, 24 December 2019
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%.
The problem
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.