Pearson distribution

E665238

continuous probability distribution probability distribution family statistical model

The Pearson distribution is a family of continuous probability distributions introduced by Karl Pearson to flexibly model data with varying skewness and kurtosis.

Try in SPARQL Jump to: Surface forms Disambiguation Statements Elicitation Referenced by

All labels observed (9)

Label	Occurrences
Pearson Type I distribution	1
Pearson Type II distribution	1
Pearson Type III distribution	1
Pearson Type IV distribution	1
Pearson Type V distribution	1
Pearson Type VII distribution	1
Pearson distribution canonical	1
Pearson system of distributions	1
Pearson type VII distribution	1

How this entity was disambiguated

This entity first appeared as the object of triple T7454019 — resolving that mention is where its identity was fixed. The disambiguator weighed these candidate entities and picked the highlighted one (or “None”, minting a new entity). This is how homonymy is resolved: the same surface form can point to different entities.

NED1 Entity disambiguation (via context triple) gpt-5-mini-2025-08-07

Target entity: Pearson distribution
Context triple: [Karl Pearson, notableWork, Pearson distribution]

A. Carsey-Werner Distribution
Carsey-Werner Distribution is a television distribution company best known for handling popular sitcoms produced by Carsey-Werner, including major hits from the late 1980s and 1990s.
B. Dirichlet distribution
The Dirichlet distribution is a family of continuous multivariate probability distributions commonly used as a prior over categorical or multinomial parameters in Bayesian statistics.
C. Tukey's lambda distribution
Tukey's lambda distribution is a flexible family of probability distributions used primarily for exploratory data analysis and modeling diverse shapes of data, including varying degrees of skewness and kurtosis.
D. Pareto distribution
The Pareto distribution is a power-law probability distribution often used to model phenomena with heavy tails and strong inequality, such as wealth or city sizes.
E. Laplace distribution
The Laplace distribution is a continuous probability distribution with a sharp peak at its mean and heavier tails than the normal distribution, often used to model data with abrupt changes or outliers.
F. None of above. chosen
G. Unsure - the case is ambiguous/there is not enough information to decide.

NED2 Entity disambiguation (via description) gpt-5-mini-2025-08-07

Target entity: Pearson distribution
Target entity description: The Pearson distribution is a family of continuous probability distributions introduced by Karl Pearson to flexibly model data with varying skewness and kurtosis.

A. Carsey-Werner Distribution
Carsey-Werner Distribution is a television distribution company best known for handling popular sitcoms produced by Carsey-Werner, including major hits from the late 1980s and 1990s.
B. Dirichlet distribution
The Dirichlet distribution is a family of continuous multivariate probability distributions commonly used as a prior over categorical or multinomial parameters in Bayesian statistics.
C. Tukey's lambda distribution
Tukey's lambda distribution is a flexible family of probability distributions used primarily for exploratory data analysis and modeling diverse shapes of data, including varying degrees of skewness and kurtosis.
D. Pareto distribution
The Pareto distribution is a power-law probability distribution often used to model phenomena with heavy tails and strong inequality, such as wealth or city sizes.
E. Laplace distribution
The Laplace distribution is a continuous probability distribution with a sharp peak at its mean and heavier tails than the normal distribution, often used to model data with abrupt changes or outliers.
F. None of above. chosen

Statements (47)

Predicate	Object
instanceOf	continuous probability distribution ⓘ probability distribution family ⓘ statistical model ⓘ
appliesTo	univariate continuous random variables ⓘ
assumes	continuous support on an interval ⓘ
belongsTo	Pearson system of distributions ⓘ linked to: Pearson distribution
canBeEstimatedBy	maximum likelihood estimation ⓘ method of moments ⓘ
characterizedBy	kurtosis ⓘ mean ⓘ skewness ⓘ variance ⓘ
definedBy	first-order differential equation for the density ⓘ
field	probability theory ⓘ statistics ⓘ
generalizes	Student t-distribution ⓘ linked to: Student’s t-distribution beta distribution ⓘ gamma distribution ⓘ normal distribution ⓘ
hasAlternativeName	Pearson system ⓘ
hasGoal	to model data with given skewness and kurtosis ⓘ
hasParameter	location parameter ⓘ scale parameter ⓘ shape parameter ⓘ
hasProperty	can approximate many common distributions ⓘ
hasSubclass	Pearson Type I distribution ⓘ linked to: Pearson distribution Pearson Type II distribution ⓘ linked to: Pearson distribution Pearson Type III distribution ⓘ linked to: Pearson distribution Pearson Type IV distribution ⓘ linked to: Pearson distribution Pearson Type V distribution ⓘ linked to: Pearson distribution Pearson Type VI distribution ⓘ Pearson Type VII distribution ⓘ linked to: Pearson distribution
hasTypeClassification	Type I–Type VII ⓘ
introducedBy	Karl Pearson ⓘ
introducedInYear	1895 ⓘ
namedAfter	Karl Pearson ⓘ
supports	flexible kurtosis ⓘ flexible skewness ⓘ
usedFor	approximating unknown distributions ⓘ fitting empirical distributions ⓘ modeling kurtotic data ⓘ modeling skewed data ⓘ
usedIn	biostatistics ⓘ finance ⓘ hydrology ⓘ quality control ⓘ reliability engineering ⓘ

How these facts were elicited