KnowraConvergence in distributionLinked fromLinked fromThe 15 pages that link to Convergence in distribution, each with the reason it gives.All 15Related 7Narrower topic 3Compared with 5Central limit theoremRelated: The theorem’s conclusion is convergence in distribution, not necessarily convergence of individual outcomes.Weak convergenceRelated: It is the probabilistic use of weak convergence for laws.Portmanteau theoremRelated: This is the probabilistic convergence notion the theorem characterizes.Slutsky's theoremRelated: This is the convergence mode preserved for the transformed random variables.Skorokhod representation theoremRelated: It is the probabilistic formulation of the theorem's weak-convergence premise.Erdős–Kac theoremRelated: The theorem asserts convergence of normalized counts as random variables, not pointwise convergence for each integer.Fisher–Tippett–Gnedenko theoremRelated: The theorem’s limits are distributional, not necessarily pointwise limits of sample values.