LLN

E582381

LLN is a fundamental theorem in probability theory stating that as the number of independent, identically distributed trials increases, the sample average converges to the expected value.

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Label Occurrences
LLN canonical 1

Statements (38)

Predicate Object
instanceOf law of large numbers
probability theorem
alsoKnownAs strong law of large numbers
weak law of large numbers
appliesTo independent identically distributed random variables
assumes finite expected value
identical distribution of trials
independence of trials
category limit theorem in probability
contrastedWith central limit theorem NERFINISHED
describes convergence of sample averages to expected value
ensures stability of long-run frequencies
field probability theory
statistics
formalization measure-theoretic probability framework
formalizes long-run average behavior of random experiments
fullName law of large numbers NERFINISHED
hasConsequence empirical mean is consistent estimator of expectation
hasVariant strong law of large numbers
weak law of large numbers NERFINISHED
historicalOrigin Jakob Bernoulli NERFINISHED
holdsUnder certain moment conditions
implies law of averages in colloquial terms
sample mean approximates population mean
mathematicalObject theorem about sequences of random variables
motivates use of sample averages in statistics
provenBy Chebyshev NERFINISHED
Kolmogorov NERFINISHED
relatedConcept Borel–Cantelli lemma NERFINISHED
Chebyshev inequality NERFINISHED
ergodic theorem
requires large number of trials
typeOfConvergence almost sure convergence
convergence in probability
usedIn Monte Carlo methods
frequentist interpretation of probability
statistical inference
yearFirstFormulated early 18th century

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