E[g(X)± h(X)] = E\g(X)] ± E[h(X)]. %3D

A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
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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The expected value of the sum or difference of two or more functions of a random
variable X is the sum or difference of the expected values of the functions. That
is,
E[g(X)±h(X)] = E[g(X)] ± E[h(X)].
Transcribed Image Text:The expected value of the sum or difference of two or more functions of a random variable X is the sum or difference of the expected values of the functions. That is, E[g(X)±h(X)] = E[g(X)] ± E[h(X)].
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