Let X and Y be independent integrable random variables on a probability space and f be a nonnegative convex function. Show that E[f(X +Y)] ≥ E[f(X +EY)]. Note. We need to apply the following Jensen’s inequality for conditional expectations. Let f be a convex function and X be an integrable random variable satisfying E|f(X)| < ∞.Thenf(E(X|A)) ≤ E(f(X)|A) a.s.

A First Course in Probability (10th Edition)
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ISBN:9780134753119
Author:Sheldon Ross
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Chapter1: Combinatorial Analysis
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Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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Let X and Y be independent integrable random variables on a probability space and f be a nonnegative convex function. Show that E[f(X +Y)] ≥ E[f(X +EY)]. Note. We need to apply the following Jensen’s inequality for conditional expectations. Let f be a convex function and X be an integrable random variable satisfying E|f(X)| < ∞.Thenf(E(X|A)) ≤ E(f(X)|A) a.s.

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