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In mathematics, the Khintchine inequality, named after Aleksandr Khinchin and spelled in multiple ways in the Latin alphabet, is a theorem from probability, and is also frequently used in analysis. Heuristically, it says that if we pick complex numbers, and add them together each multiplied by a random sign , then the expected value of the sum's modulus, or the modulus it will be closest to on average, will be not too far off from .
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E1.10 The Weak Law of Large Numbers (Econometrics Math)
MIT 6.854 Spring 2016 Lecture 20: Grothendieck's Inequality and the Lovasz Theta Function
for some constants depending only on (see Expected value for notation). The sharp values of the constants were found by Haagerup (Ref. 2; see Ref. 3 for a simpler proof). It is a simple matter to see that when , and when .
The uses of this inequality are not limited to applications in probability theory. One example of its use in analysis is the following: if we let be a linear operator between two Lp spaces and , , with bounded norm, then one can use Khintchine's inequality to show that
^Pawel Hitczenko, "On the Rademacher Series". Probability in Banach Spaces, 9 pp 31-36. ISBN978-1-4612-0253-0
Thomas H. Wolff, "Lectures on Harmonic Analysis". American Mathematical Society, University Lecture Series vol. 29, 2003. ISBN0-8218-3449-5
Uffe Haagerup, "The best constants in the Khintchine inequality", Studia Math. 70 (1981), no. 3, 231–283 (1982).
Fedor Nazarov and Anatoliy Podkorytov, "Ball, Haagerup, and distribution functions", Complex analysis, operators, and related topics, 247–267, Oper. Theory Adv. Appl., 113, Birkhäuser, Basel, 2000.
This page was last edited on 30 January 2024, at 06:00