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CH 9

This document discusses several probability and statistics concepts including: why the probability mass function of a joint distribution equals the marginal distribution of one of the random variables; why we do not sum over all values of a random variable; the difference between independent random processes and having different independent and identically distributed random processes; and finding the covariance matrix and mean vector as the solution for a particular problem.

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kadry mohamed
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68 views4 pages

CH 9

This document discusses several probability and statistics concepts including: why the probability mass function of a joint distribution equals the marginal distribution of one of the random variables; why we do not sum over all values of a random variable; the difference between independent random processes and having different independent and identically distributed random processes; and finding the covariance matrix and mean vector as the solution for a particular problem.

Uploaded by

kadry mohamed
Copyright
© © All Rights Reserved
We take content rights seriously. If you suspect this is your content, claim it here.
Available Formats
Download as PDF, TXT or read online on Scribd
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Why PMF of joint = marginal of P (N)

Why we do not sum over all value of n

In d the transformation is the identity matrix


In problem 1 the rvs are not independent so why we test law of large
number.

why g(t + T) = 0 for t+T outside (0,1)

What is the different between Independent random process and, have different
iid RPs
Why in b is no Ind increment

Why g(u) = 1 or 0 it must be continuous


The solution for c that I should find the covariance matrix and mean vector

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