A Course in Probability Theory (3rd Edition) by Kai Lai Chung

By Kai Lai Chung

Because the booklet of the 1st variation of this vintage textbook over thirty years in the past, tens of millions of scholars have used A direction in chance Theory. New during this version is an creation to degree conception that expands the marketplace, as this remedy is extra in keeping with present classes.

While there are numerous books on chance, Chung's booklet is taken into account a vintage, unique paintings in likelihood thought as a result of its elite point of sophistication.

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Extra resources for A Course in Probability Theory (3rd Edition)

Example text

Expectation. 1 General definitions Let the probability space , F , P be given. R1 D 1, C1 the (finite) Ł real line, R D [ 1, C1] the extended real line, B1 D the Euclidean Borel field on R1 , BŁ D the extended Borel field. A set in BŁ is just a set in B possibly enlarged by one or both points š1. DEFINITION OF A RANDOM VARIABLE. A real, extended-valued random variable is a function X whose domain is a set 1 in F and whose range is contained in RŁ D [ 1, C1] such that for each B in BŁ , we have 1 fω: X ω 2 Bg 2 1 \ F where 1 \ F is the trace of F on 1.

Since lim sup Xj D inf sup Xj , j n j½n 40 RANDOM VARIABLE. EXPECTATION. 1 Xj exists [and is finite] on the set where lim supj Xj D lim infj Xj [and is finite], which belongs to F , the rest follows. v. given at the beginning of this section. DEFINITION. v. X is called discrete (or countably valued ) iff there is a countable set B ² R1 such that P X 2 B D 1. f. is. v. need not have a range that is discrete in the sense of Euclidean topology, even apart from a set of probability zero. v. f. in Example 2 of Sec.

4) we note the following extension. Let P be defined on a field F which is finitely additive and satisfies axioms (i), (iii), and (1). Then (ii) holds whenever k Ek 2 F . For then 1 kDnC1 Ek also belongs to F , and the second part of the proof above remains valid. The triple , F , P is called a probability space (triple); alone is called the sample space, and ω is then a sample point. F. F on 1 is the collection of all sets of the form 1 \ F, where F 2 F . F. of subsets of 1, and we shall denote it by 1 \ F .

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