In probability theory, Kolmogorov's inequality is a so-called "maximal inequality" that gives a bound on the probability that the partial sums of a finite collection of independent random variables exceed some specified bound.
 The inequality is named after the Russian mathematician Andrey Kolmogorov.
In mathematics, Kolmogorov's normability criterion is a theorem that provides a necessary and sufficient condition for a topological vector space to be normable, i.e. for the existence of a norm on the space that generates the given topology.
 The normability criterion can be seen as a result in same vein as the Nagata–Smirnov metrization theorem, which gives a necessary and sufficient condition for a topological space to be metrizable.
 The result was proved by the Russian mathematician Andrey Nikolayevich Kolmogorov in 1934.
In Kolmogorov's probability theory, the probability "P" of some event "E", denoted formula_1, is usually defined such that "P" satisfies the Kolmogorov axioms, named after the Russian mathematician Andrey Kolmogorov, which are described below.
Andrey Nikolaevich Kolmogorov (Russian: Андрей Николаевич Колмогоров ; ] , 25 April 1903 – 20 October 1987) was a 20th-century Soviet mathematician who made significant contributions to the mathematics of probability theory, topology, intuitionistic logic, turbulence, classical mechanics, algorithmic information theory and computational complexity.
In mathematics, specifically in the theory of Markovian stochastic processes in probability theory, the Chapman–Kolmogorov equation is an identity relating the joint probability distributions of different sets of coordinates on a stochastic process.
 The equation was derived independently by both the British mathematician Sydney Chapman and the Russian mathematician Andrey Kolmogorov.
In mathematics, the Hahn–Kolmogorov theorem characterizes when a finitely additive function with non-negative (possibly infinite) values can be extended to a "bona fide" measure.
 It is named after the Austrian mathematician Hans Hahn and the Russian/Soviet mathematician Andrey Kolmogorov.
In mathematics, the Kolmogorov extension theorem (also known as Kolmogorov existence theorem or Kolmogorov consistency theorem) is a theorem that guarantees that a suitably "consistent" collection of finite-dimensional distributions will define a stochastic process.
 It is credited to the Russian mathematician Andrey Nikolaevich Kolmogorov.
In mathematics, the Kolmogorov continuity theorem is a theorem that guarantees that a stochastic process that satisfies certain constraints on the moments of its increments will be continuous (or, more precisely, have a "continuous version").
 It is credited to the Soviet mathematician Andrey Nikolaevich Kolmogorov.
Boris Vladimirovich Gnedenko (Russian: Бори́с Влади́мирович Гнеде́нко ; January 1, 1912 – December 27, 1995) was a Soviet mathematician and a student of Andrey Nikolaevich Kolmogorov.
 He was born in Simbirsk (now Ulyanovsk), Russia, and died in Moscow.
 He is perhaps best known for his work with Kolmogorov, and his contributions to the study of probability theory, particularly extreme value theory, with such results as the Fisher–Tippett–Gnedenko theorem.
 Gnedenko was appointed as Head of the Physics, Mathematics and Chemistry Section of the Ukrainian Academy of Sciences in 1949, and also became Director of the Kiev Institute of Mathematics in the same year.
In mathematics and statistics, the quasi-arithmetic mean or generalised "f"-mean is one generalisation of the more familiar means such as the arithmetic mean and the geometric mean, using a function formula_1.
 It is also called Kolmogorov mean after Russian mathematician Andrey Kolmogorov.

Question: In which century did the mathematician that created the Kolmogorov continuity theorum live?
Answer: 20th-century