Probability axioms in the context of "Random sequence"


Probability axioms in the context of "Random sequence"

Probability axioms Study page number 1 of 1

Answer the Probability Axioms Trivia Question!

or

Skip to study material about Probability axioms in the context of "Random sequence"


⭐ Core Definition: Probability axioms

The standard probability axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. Like all axiomatic systems, they outline the basic assumptions underlying the application of probability to fields such as pure mathematics and the physical sciences, while avoiding logical paradoxes.

The probability axioms do not specify or assume any particular interpretation of probability, but may be motivated by starting from a philosophical definition of probability and arguing that the axioms are satisfied by this definition. For example,

↓ Menu
HINT:

👉 Probability axioms in the context of Random sequence

The concept of a random sequence is essential in probability theory and statistics. The concept generally relies on the notion of a sequence of random variables and many statistical discussions begin with the words "let X1,...,Xn be independent random variables...". Yet as D. H. Lehmer stated in 1951: "A random sequence is a vague notion... in which each term is unpredictable to the uninitiated and whose digits pass a certain number of tests traditional with statisticians".

Axiomatic probability theory deliberately avoids a definition of a random sequence. Traditional probability theory does not state if a specific sequence is random, but generally proceeds to discuss the properties of random variables and stochastic sequences assuming some definition of randomness. The Bourbaki school considered the statement "let us consider a random sequence" an abuse of language.

↓ Explore More Topics
In this Dossier