Normal frequency distribution: Difference between revisions
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A normal frequency distribution is a continuous, symmetrical, bell-shaped distribution function. | A normal frequency distribution is a theoretical continuous, symmetrical, bell-shaped distribution function. | ||
Its mean, mode and median are all the same; and both the tails of the bell curve are infinitely long. | Its mean, mode and median are all the same; and both the tails of the bell curve are infinitely long. | ||
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Commonly abbreviated to ''normal distribution''. | Commonly abbreviated to ''normal distribution''. | ||
Simple normal distributions are frequently used for modelling uncertainty. However, reality is rarely so neat and symmetrical as the normal distribution model. | |||
This can lead to spurious accuracy and a false sense of security from relying on models of that kind. | |||
== See also == | == See also == | ||
* [[Binomial]] | * [[Binomial]] | ||
* [[Distribution]] | |||
* [[Fat tail]] | |||
* [[Frequency distribution]] | * [[Frequency distribution]] | ||
* [[Kurtosis]] | * [[Kurtosis]] | ||
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* [[Lognormal frequency distribution]] | * [[Lognormal frequency distribution]] | ||
* [[Mean]] | * [[Mean]] | ||
* [[Mode]] | |||
* [[Median]] | |||
* [[Skewness]] | |||
* [[Standard deviation]] | * [[Standard deviation]] | ||
* [[Standardised normal distribution]] | * [[Standardised normal distribution]] | ||
* [[Tail event]] | |||
* [[Tail risk]] | |||
* [[Value at risk]] | |||
===Other links=== | |||
[http://www.treasurers.org/node/9214 Students: Perfect proportions, The Treasurer, July 2013] | |||
[[Category:Financial_risk_management]] | |||
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Latest revision as of 21:24, 18 September 2021
A normal frequency distribution is a theoretical continuous, symmetrical, bell-shaped distribution function. Its mean, mode and median are all the same; and both the tails of the bell curve are infinitely long.
Because of its symmetry, a normal frequency distribution can be described fully by its mean and its standard deviation.
Commonly abbreviated to normal distribution.
Simple normal distributions are frequently used for modelling uncertainty. However, reality is rarely so neat and symmetrical as the normal distribution model.
This can lead to spurious accuracy and a false sense of security from relying on models of that kind.
See also
- Binomial
- Distribution
- Fat tail
- Frequency distribution
- Kurtosis
- Leptokurtic frequency distribution
- Lognormal frequency distribution
- Mean
- Mode
- Median
- Skewness
- Standard deviation
- Standardised normal distribution
- Tail event
- Tail risk
- Value at risk
