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1.2.12. Accept the following definition. Discrete random variables X1, X2,.. ,...
3. Let X1, X2, . . . , Xn be random variables with a common mean...
3. Let X1, X2, . . . , Xn be random variables with a common mean μ. Sup- pose that cov[Xi, xj] = 0 for all i and A such that j > i+1. If 仁1 and 6 VECTORS OF RANDOM VARIABLES prove that = var X n(n- 3)
explan the answer 1l. Suppose that X1, X2,... Xn are independent random variables. Assume that ElXi]...
explan the answer
1l. Suppose that X1, X2,... Xn are independent random variables. Assume that ElXi] /4 and Var(X )-σ, where i 1, 2, . .., n. If ai , aam. , an are constants. 1,a2, , an are constan (i) Write down expression for (i) E{Σ,i ai Xi) and (ii) Var(Li la(Xi). (i) Rewrite the expression if X,'s are not independent.
(10 marks) Let X1, X2,... be a sequence of independent and identically distributed random variables with...
(10 marks) Let X1, X2,... be a sequence of independent and identically distributed random variables with mean EX1 = i and VarX1 = a2. Let Yı, Y2, ... be another sequence of independent and identically distributed random variables with mean EY = u and VarY1 a2 Define the random variable ( ΣxΣ) 1 Dn 2ng2 i= i=1 Prove that Dn converges in distribution to a standard normal distribution, i.e., prove that 1 P(Dn ) dt 2T as n >oo for...
Suppose X1, X2,... are independent Geometric (number of trials) random variables where Xi ~ Geome...
Suppose X1, X2,... are independent Geometric (number of trials)
random variables where Xi ~ Geometric(p = 1/i^2)
a) It is easily shown that Xn converges to a for some constant
a. Name it.
b) According to the Borel-Cantelli Lemmas, does Xn almost surely
converge to a?
Suppose Xi, X2, are independent Geometric (number of trials) random variables where x,~ Geometric(pal+) |. a) It is easily shown that Xa for some constant a. Name it. b) According to the Borel-Cantelli Lemmas,...
Let X1 and X2 be two discrete random variables, where X1 can attain values 1, 2,...
Let X1 and X2 be two discrete random variables, where X1 can
attain values 1, 2, and 3, and X2 can attain values 2, 3 and 4. The
joint probability mass function of these two random variables are
given in the table below: X2 X1 2 3 4 1 0.05 0.04 0.06 2 0.1 0.15
0.2 3 0.2 0.1 0.1 a. Find the marginal probability mass functions
fX1 (s) and fX2 (t). b. What is the expected values of X1...
L.11) Sums of independent random variables a) If X1 , X2 X, , , Xn are...
L.11) Sums of independent random variables a) If X1 , X2 X, , , Xn are independent random variables all with Exponential μ distribution, then what is the distribution of XII + 2 +X3 + .tX b) If X is a random variable with Exponential[u] distribution, then what is the distribution of x +X1? c) If X1 , X2 , Х, , , X are independent random variables all with Normal 0. I distribution, then what is the distribution of...
Suppose X1, X2, . . . are independent discrete random variables, having the same distribution, and...
Suppose X1, X2, . . . are independent discrete random variables,
having the same distribution, and E[Xi] > 0, for each i. Is thus
true for any two positive integers n and m?:
Why not, or why yes?
1. Let X1, ... , Xn be independent random variables taking values 0 or 1 with...
1. Let X1, ·s, Xn be independent random variables taking values 0 or 1 withP(Xi=1)=eθ-ai /(1+eθ-ai ), i=1, ……, nfor some given constants ai. Find a one-dimensional sufficient statistic for θ.
Let X1 and X2 be random variables, not necessarily independent. Show that E [X1 + X2]...
Let X1 and X2 be random variables, not necessarily independent. Show that E [X1 + X2] = E [X1] + E [X2]. You may assume that X1 and X2 are discrete with a joint probability mass function for this problem, while the above inequality is true also for continuous random variables.
4. Let Xi, X2,... be uncorrelated random variables, such that Xn has a uniform distribution over...
4. Let Xi, X2,... be uncorrelated random variables, such that Xn has a uniform distribution over -1/n, 1/n]. Does the sequence converge in probability? 5. Let Xi,X2 be independent random variables, such that P(X) PX--) Does the sequence X1 +X2+...+X satisfy the WLLN? Converge in probability to 0?
3. Let X1, X2, . . . , Xn be random variables with a common mean μ. Sup- pose that cov[Xi, xj] = 0 for all i and A such that j > i+1. If 仁1 and 6 VECTORS OF RANDOM VARIABLES prove that = var X n(n- 3)
explan the answer
1l. Suppose that X1, X2,... Xn are independent random variables. Assume that ElXi] /4 and Var(X )-σ, where i 1, 2, . .., n. If ai , aam. , an are constants. 1,a2, , an are constan (i) Write down expression for (i) E{Σ,i ai Xi) and (ii) Var(Li la(Xi). (i) Rewrite the expression if X,'s are not independent.
(10 marks) Let X1, X2,... be a sequence of independent and identically distributed random variables with mean EX1 = i and VarX1 = a2. Let Yı, Y2, ... be another sequence of independent and identically distributed random variables with mean EY = u and VarY1 a2 Define the random variable ( ΣxΣ) 1 Dn 2ng2 i= i=1 Prove that Dn converges in distribution to a standard normal distribution, i.e., prove that 1 P(Dn ) dt 2T as n >oo for...
Suppose X1, X2,... are independent Geometric (number of trials)
random variables where Xi ~ Geometric(p = 1/i^2)
a) It is easily shown that Xn converges to a for some constant
a. Name it.
b) According to the Borel-Cantelli Lemmas, does Xn almost surely
converge to a?
Suppose Xi, X2, are independent Geometric (number of trials) random variables where x,~ Geometric(pal+) |. a) It is easily shown that Xa for some constant a. Name it. b) According to the Borel-Cantelli Lemmas,...
Let X1 and X2 be two discrete random variables, where X1 can
attain values 1, 2, and 3, and X2 can attain values 2, 3 and 4. The
joint probability mass function of these two random variables are
given in the table below: X2 X1 2 3 4 1 0.05 0.04 0.06 2 0.1 0.15
0.2 3 0.2 0.1 0.1 a. Find the marginal probability mass functions
fX1 (s) and fX2 (t). b. What is the expected values of X1...
L.11) Sums of independent random variables a) If X1 , X2 X, , , Xn are independent random variables all with Exponential μ distribution, then what is the distribution of XII + 2 +X3 + .tX b) If X is a random variable with Exponential[u] distribution, then what is the distribution of x +X1? c) If X1 , X2 , Х, , , X are independent random variables all with Normal 0. I distribution, then what is the distribution of...
Suppose X1, X2, . . . are independent discrete random variables,
having the same distribution, and E[Xi] > 0, for each i. Is thus
true for any two positive integers n and m?:
Why not, or why yes?
1. Let X1, ·s, Xn be independent random variables taking values 0 or 1 withP(Xi=1)=eθ-ai /(1+eθ-ai ), i=1, ……, nfor some given constants ai. Find a one-dimensional sufficient statistic for θ.
4. Let Xi, X2,... be uncorrelated random variables, such that Xn has a uniform distribution over -1/n, 1/n]. Does the sequence converge in probability? 5. Let Xi,X2 be independent random variables, such that P(X) PX--) Does the sequence X1 +X2+...+X satisfy the WLLN? Converge in probability to 0?
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