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gptkbp:instanceOf
|
statistical theorem
|
|
gptkbp:appliesTo
|
independent and identically distributed random variables
|
|
gptkbp:category
|
gptkb:probability_theory
|
|
gptkbp:describes
|
distribution of sample means
|
|
gptkbp:developedBy
|
gptkb:Carl_Friedrich_Gauss
gptkb:Pierre-Simon_Laplace
gptkb:Aleksandr_Lyapunov
|
|
gptkbp:field
|
statistics
|
|
gptkbp:formedBy
|
gptkb:Abraham_de_Moivre
|
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gptkbp:generalizes
|
gptkb:Lindeberg–Feller_theorem
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|
https://www.w3.org/2000/01/rdf-schema#label
|
Central Limit Theorem
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gptkbp:implies
|
sampling distribution of the mean is approximately normal
|
|
gptkbp:namedAfter
|
centrality of the normal distribution
|
|
gptkbp:relatedTo
|
gptkb:normal_distribution
gptkb:law_of_large_numbers
|
|
gptkbp:requires
|
finite mean
finite variance
|
|
gptkbp:state
|
sum of a large number of independent random variables tends toward a normal distribution
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|
gptkbp:usedIn
|
hypothesis testing
inferential statistics
confidence intervals
|
|
gptkbp:bfsParent
|
gptkb:Central_Limit_Theorem_(early_form)
gptkb:Probability_Machine_(Galton_board)
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gptkbp:bfsLayer
|
7
|