1 Given two random variables X and Y , prove the following. (a) The covariance of X and Y can be equivalently written as
Cov(X,Y ) = E[(X x)(Y y)]
or as
Cov(X,Y ) = E[XY ] E[X]E[Y ]
where x = E[X] and y = E[Y ].
- If X and Y are independent, then X and Y are uncorrelated.
- Var(sX) = s2 Var(X) for some scalar s
- Var(X + Y ) = Var(X) + Var(Y ) + 2 Cov(X,Y )
2 (10 points) Consider a vector-valued random variable
A = Xe1 + Y e2
where e1 and e2 are the orthogonal Cartesian unit vectors, and X and Y are real-valued random variables with
X,Y N(0,2).
The random variable
R = ||A||2
is then distributed according to the Rayleigh distribution,
R Rayleigh(2).
Derive the analytic expression of the Rayleigh distribution, and write a MATLAB program that generates points from the Rayleigh distribution. Make a plot of the distribution and a histogram of the points you generated.
Note: For any of the above problems for which you use MATLAB to help you solve, you must submit your code/.m-files as part of your work. Your code must run in order to receive full credit. If you include any plots, make sure that each has a title, axis labels, and readable font size, and include the final version of your plots as well as the code used to generate them.
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