Probability with Engineering Applications - Problem Set #13 | ECE 313, Assignments of Statistics

Material Type: Assignment; Class: Probability with Engrg Applic; Subject: Electrical and Computer Engr; University: University of Illinois - Urbana-Champaign; Term: Fall 2003;

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University of Illinois Fall 2003
ECE 313: Problem Set #13
Assigned: Friday, December 5, 2003
Due: Friday, December 12, 2003
1. Assume that Var(X1+X2+X3) = Var(X1) + Var(X2) + Var(X3). Can we conclude that
X1,X2, and X3are pairwise uncorrelated? Why?
2. Let E[X] = 1, E[Y] = 4, Var(X) = 4, Var(Y) = 9, and ρX,Y = 0.1.
(a) If Z= 2(X+Y)(XY), find E[Z].
(b) If T= 2X+Yand U= 2XY, find Cov(T, U ).
(c) If W= 3X+Y+ 2, find E[W] and Var(W).
3. Assume that the density function fX(u) of a random variable Xis an even function, and
that E(X2)<. Show that (a) |X|and Xare uncorrelated, and (b) |X|and Xare not
independent.
4. Let X1, X2, . . . , Xnbe independent and identically distributed positive RVs. Show that for
kn,
E"Pk
i=1 Xi
Pn
i=1 Xi#=k
n.
5. Let X1, X2,··· be an infinite sequence of independent, identically distributed, random
variables with mean µand variance σ2. We define Yn=Xn+Xn+1 +Xn+2, for n= 1,2,···.
For each k0, compute Cov(Yn, Yn+k).
6. Suppose that Xand Yare jointly Gaussian random variables. It is further known that:
E[X] = 0, E[Y] = 0,Var(X) = σ2
1,Var(Y) = σ2
2, ρ(X, Y ) = ρ.
Find an angle θsuch that Z=Xcos θ+Ysin θand W=Ycos θXsin θare independent
Gaussian random variables. You may express your answer in terms of a trigonometric
function of σ1, σ2and ρ. In particular, what is the value of θif σ1=σ2?
7. Extra Credit: Show that |Cov(X, Y )|2Var(X)Var(Y), where the equality holds if and
only if Y=aX +bwith aand bbeing some arbitrary constants.
8. Extra Credit: Let X1and X2be independent RVs with the same distribution N(µ, σ2).
Show that E[max{X1, X2}] = µ+σ/π.

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University of Illinois Fall 2003

ECE 313: Problem Set

Assigned: Friday, December 5, 2003 Due: Friday, December 12, 2003

  1. Assume that Var(X 1 + X 2 + X 3 ) = Var(X 1 ) + Var(X 2 ) + Var(X 3 ). Can we conclude that X 1 , X 2 , and X 3 are pairwise uncorrelated? Why?
  2. Let E[X] = 1, E[Y ] = 4, Var(X) = 4, Var(Y ) = 9, and ρX,Y = 0.1.

(a) If Z = 2(X + Y )(X − Y ), find E[Z]. (b) If T = 2X + Y and U = 2X − Y , find Cov(T, U ). (c) If W = 3X + Y + 2, find E[W ] and Var(W ).

  1. Assume that the density function fX (u) of a random variable X is an even function, and that E(X^2 ) < ∞. Show that (a) |X| and X are uncorrelated, and (b) |X| and X are not independent.
  2. Let X 1 , X 2 ,... , Xn be independent and identically distributed positive RVs. Show that for k ≤ n,

E

[ ∑k ∑i=1^ Xi n i=1 Xi

]

k n

  1. Let X 1 , X 2 , · · · be an infinite sequence of independent, identically distributed, random variables with mean μ and variance σ^2. We define Yn = Xn + Xn+1 + Xn+2, for n = 1, 2 , · · ·. For each k ≥ 0, compute Cov(Yn, Yn+k).
  2. Suppose that X and Y are jointly Gaussian random variables. It is further known that:

E[X] = 0, E[Y ] = 0, Var(X) = σ^21 , Var(Y ) = σ^22 , ρ(X, Y ) = ρ.

Find an angle θ such that Z = X cos θ + Y sin θ and W = Y cos θ − X sin θ are independent Gaussian random variables. You may express your answer in terms of a trigonometric function of σ 1 , σ 2 and ρ. In particular, what is the value of θ if σ 1 = σ 2?

  1. Extra Credit: Show that |Cov(X, Y )|^2 ≤ Var(X)Var(Y ), where the equality holds if and only if Y = aX + b with a and b being some arbitrary constants.
  2. Extra Credit: Let X 1 and X 2 be independent RVs with the same distribution N (μ, σ^2 ). Show that E[max{X 1 , X 2 }] = μ + σ/

π.