CLT:中心极限定理(概率论)
中心极限定理(Central Limit Theorem,简称CLT)是概率论与统计学中的一项重要理论,广泛应用于各类科学研究及数学分析中。该定理指出,在特定条件下,大量独立随机变量的均值分布会趋近于正态分布。为便于快速书写与学术交流,其英文名称常缩写为CLT。
Central Limit Theorem ( probability theory)具体释义
Central Limit Theorem ( probability theory)的英文发音
例句
- The classical central limit theorem is an essential foundation of probability theory. It is extensively applied to statistics, nature sciences, engineering and economics.
- 经典的中心极限定理是概率论的重要基础,它广泛应用于统计、自然科学、工程学和经济学。
- The almost sure central limit theorem and self-normalized limit theory have become two important fields of the study of probability limit theory in recent decades.
- 而对几乎处处极限定理和自赋范极限理论的研究则是近几十年来概率极限理论研究中的两个重要方向。
- The theorem of large and the related theory were strictly proved by PMS, the theory system of the classical central limit theorem was consummated, the model and the theory of Markov chain were established, and the axioms of probability theory was proposed for the first time.
- 在其概率思想指导下,彼得堡数学学派严格论证了大数定理理论、完善了古典中心极限定理的理论体系、创立了马尔可夫链模型、发展了数理统计理论、首次提出概率论的公理化体系等。
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