Suppose that X has an arbitrary discrete distribution, symmetric about zero and having its third moment...
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2. Let X and Y be discrete random variables taking values 0 or 1 only, and let pr(X = i, Y = j)-pij (jz 1,0;j = 1,0). Prove that X and Y are independent if and only if cov[X,Y) 0 3. If X is a random variable with a density function symmetric about zero and having zero mean, prove that cov[X, X2] 0.
1 Let X be a discrete random variable. (a) Show that if X has a finite mean μ. then EX-ix-0. (b) Show that if X has a finite variance, then its mean is necessarily finite 2 Let X and Y be random variables with finite mean. Show that, if X and Y are independent, then 3 Let Y have mean μ and finite variance σ2 (a) Use calculus to show that μ is the best predictor of Y under quadratic...
1. Let X and Y have a discrete joint distribution with ( P(X = x, Y = y) = {1, 10, if (x, y) = (-1,1) if x = y = 0 elsewhere Show that X and Y are uncorrelated but not independent. [5 points] 2. Let X and Y have a discrete joint distribution with f(-1,0) = 0, f(-1,1) = 1/4, f(0,0) = 1/6, f(0, 1) = 0, $(1,0) = 1/12, f(1,1) = 1/2. Show that (a) the two...
3. Suppose X, Y are discrete random variables taking values in -1,0,1) and their joint probability mass function is 0 0 0 where a, b are two positive real numbers. (i) Find the values of a and b such that X and Y are uncorrelated (ii) Show that X and Y cannot be independent
3. Suppose X, Y are discrete random variables taking values in {-1,0,1) and their joint probability mass function is 0 X=1 where a, b are two positive real numbers. (i) Find the values of a and b such that X and Y are uncorrelated. (ii) Show that X and Y cannot be independent 0
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3. Suppose X, Y are discrete random variables taking values in-1,0, 1) and their joint probability mass function is 0 0 X=1 where a, b are two positive real numbers (i) Find the values of a and b such that X and Y are uncorrelated (ii) Show that X and Y cannot be independent. 0
Suppose X, Y and Z are three different random variables. Let X obey Bernoulli Distribution. The probability distribution function is p(x) = Let Y obeys the standard Normal (Gaussian) distribution, which can be written as Y ∼ N(0, 1). X and Y are independent. Meanwhile, let Z = XY . (a) What is the Expectation (mean value) of X? (b) Are Y and Z independent? (Just clarify, do not need to prove) (c) Show that Z is also a standard...
The discrete random variables X and Y take integer values with joint probability distribution given by f (x,y) = a(y−x+1) 0 ≤ x ≤ y ≤ 2 or =0 otherwise, where a is a constant. 1 Tabulate the distribution and show that a = 0.1. 2 Find the marginal distributions of X and Y. 3 Calculate Cov(X,Y). 4 State, giving a reason, whether X and Y are independent. 5 Calculate E(Y|X = 1).
4. The moment generating function of the normal distribution with parameters μ and σ2 is (t) exp ( μ1+ σ2t2 ) for -oo < t oo. Show that E X)-ψ(0)-μ and Var(X)-ψ"(0)-[ty(0)12-σ2. 5. Suppose that X1, X2, and X3 are independent random variables such that E[X]0 and ElX 1 for i-12,3. Find the value of E[LX? (2X1 X3)2] 6. Suppose that X and Y are random variables such that Var(X)-Var(Y)-2 and Cov(X, Y)- 1. Find the value of Var(3X -...
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2. If X has a Gamma distribution with parameters a and B, then its mgf is given by (a) Obtain expressions for the moment-genérating functions of an exponential random variable and of a chi-square random variable by recognizing that these are special cases of a Gamma distribution and using the mgf given above. (b) Suppose that X1 is a Gamma variable with parameters α1 and β, X2 is a Gamma variable with parameters...