Triple

Target class: law of large numbers
Context triple: [LLN, instanceOf, law of large numbers]

• A. central limit theorem
  The central limit theorem states that, under broad conditions, the sum (or average) of a large number of independent, identically distributed random variables tends to follow a normal distribution, regardless of the original variables’ distribution.
• B. quantitative central limit theorem
  The quantitative central limit theorem provides explicit bounds on how quickly the distribution of normalized sums of random variables converges to the normal distribution, typically in terms of metrics like the Kolmogorov or Wasserstein distance.
• C. result in probability theory chosen
  In probability theory, a result is a formally stated and proven fact—such as a theorem, lemma, or corollary—that describes a property or relationship involving probabilistic concepts like random variables, events, or distributions.
• D. tool in large deviation theory
  A tool in large deviation theory is a mathematical method or result—such as rate functions, the Gartner–Ellis theorem, or contraction principles—used to quantify and analyze the exponentially small probabilities of rare events in stochastic systems.
• E. probability rule
  A probability rule is a fundamental principle that defines how probabilities are assigned, combined, and manipulated within a probabilistic system to ensure consistency and coherence.
• F. None of above.