(a) TRUE / FALSE If X is a random variable, then (E[X])^2 ≤
E[X^2]. (b) TRUE...
(a) TRUE / FALSE If X is a random variable, then (E[X])^2 ≤
E[X^2]. (b) TRUE / FALSE If Cov(X,Y) = 0, then X and Y are
independent. (c) TRUE / FALSE If P(A) = 0.5 and P(B) = 0.5, then
P(AB) = 0.25. (d) TRUE / FALSE There exist events A,B with P(A)not
equal to 0 and P(B)not equal to 0 for which A and B are both
independent and mutually exclusive. (e) TRUE / FALSE Var(X+Y) =
Var(X)...
Let the random variable X and Y have the joint pmf f(x, y) =
xy^2/c where...
Let the random variable X and Y have the joint pmf f(x, y) =
xy^2/c where x = 1, 2, 3; y = 1, 2, x + y ≤ 4 , that is, (x, y) are
{(1, 1),(1, 2),(2, 1),(2, 2),(3, 1)} .
(a) Find c > 0 .
(b) Find μX
(c) Find μY
(d) Find σ^2 X
(e) Find σ^2 Y
(f) Find Cov (X, Y )
(g) Find ρ , Corr (X, Y )
(h) Are X...
(a) It is given that a random variable X such that P(X =−1) =P(X
= 1)...
(a) It is given that a random variable X such that P(X =−1) =P(X
= 1) = 1/4, P(X = 0) = 1/2. Find the mgf of X, mX(t)
(b) Let X1 and X2 be two iid random varibles such that P(Xi
=1)=P(Xi =−1)=1/2, i=1,2. Use the mgfs to prove that X and Y
=(X1+X2)/2 have the same distribution
Let X be a discrete random variable with the pmf
p(x): 0.8 for x=-4,
0.1 for...
Let X be a discrete random variable with the pmf
p(x): 0.8 for x=-4,
0.1 for x=-2,
0.07 for x=0,
0.03 for x=2
a) Find E(2/X)
b) Find E(lXl)
c) Find Var(lXl)
A. (i) Consider the random variable X with pmf: pX (−1) = pX (1)
= 1/8,...
A. (i) Consider the random variable X with pmf: pX (−1) = pX (1)
= 1/8, pX (0) = 3/4.
Show that the Chebyshev inequality P (|X − μ| ≥ 2σ) ≤ 1/4 is
actually an equation for
this random variable.
(ii) Find the pmf of a different random variable Y that also takes
the values {−1, 0, 1}
for which the Chebyshev inequality P (|X − μ| ≥ 3σ) ≤ 1/9 is
actually an equation.
Suppose a random variable X takes on the value of -1 or 1, each
with the...
Suppose a random variable X takes on the value of -1 or 1, each
with the probability of 1/2. Let y=X1+X2+X3+X4, where X1,....X4 are
independent. Find E(Y) and Find Var(Y)