4.144 Consider a random variable Y with density function given by f(y)=ke-²/2 a Find k. b Find the moment-generating function of Y. c Find E(Y) and V (Y). -∞
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- 5. A continuous random variable X that can assume value between x-2 and x-5 has a density function given by 1+x f(x) = 8 a. Show that P(23. Let X and Y be random variables with joint density function. fxy(x, y) = a(x+2y), 0 5V). 2vA random process {X(t)} is given by X(t) = A cos pt + B sin pt, where A and B are independent RVs such that E(A) = E(B) = 0 and E(A²) = E(B²) = o². Find the power spectral density of the process I %3D(11) When the conditional density of X given Y = y E (0, 1) is 2x fx\Y=y (x) = y < x < 1. 1 – y² ’ Compute E(X|Y = 0.25). 0.7 0.25 0.75 None of the above N/A (Select One)3.1 Solve the below problem: (9) Let Y, and Y2 have a joint density function given by 0 < y2 < y1 S 1 elsewhere. (3y1 f(v,,y2) = {" 3.1.3. Let Y, and Y2 denote random variables. Use the formula E(Y,) = E[E(Y,|Y2)] to find E (Y,). 3.1.4. Use the marginal density function of Y, to find E(Y2) to verify the answer in (3.1.3.).2. A particle of mass, m, has the wavefunction given by: (x, t) = Ce-a[(mx²/h) + it] . (a) Sketch Re [(x,0)] as a function of x. (b) Sketch Re [p(0, t)] as a function of t. (c) Sketch the probability density for finding the particle at x at t = 0. (d) Explain the time dependence in the probability density for locating the particle in space. (e) Find C (f) Find (x) (g) Find (x2) (h) Find ox (i) Find (p) (j) Find (p?) (k) Find op (1) Is the product, O,0, consistent with the Heisenberg uncertainty principle? (m) Find Tiid Let X1,· where f(xi, Find the log-likelihood .function ., Xn * f(x;, 0), • 0) = Q³e-o°zi O 93n e-0°x; 3nln (θ) e- ' Σ 3nln(0) – 0 C–1 *; i=1 3nln(0) – 0šn xi O NoneLet X1, .., Xn be a random sample from a population with 0 unknown and given by the density = * itz>0 { e f(x; 8) if x (Ə ln(f(X;0) nEtEx. 4. Let X,Y are independent random variables where X ~ N(0, 1) and Y ~ G(1/2, n/2). Let T:= X//Y/n, then show that the density function of T is described as r(n+1)/2) (1+) VnnI'(n/2) -(n+1)/2 fr(t) - (-∞3. Let X₁, X2, Xn represent a random sample from a Rayleigh distribution with proba- bility density function given below. ...9 X f(x) = -=- e – x² / (20) Ө (a) Show that E(X²) = 20. Look up the gamma function, I(z) = f* 9 x > 0 t²-¹e-t dt. (b) Find E (Σ½-1 X²) and hence find an unbiased estimator of 0. i=1 (c) Estimate from the following observations using the estimator found in part (b). 16.88 10.23 4.59 6.66 13.68 14.23 19.87 9.40 6.51 10.95E The density function of a continuous Random variable X is fx (x) = ax 0 Sx <1 for for 1Recommended textbooks for youA First Course in Probability (10th Edition)ProbabilityISBN:9780134753119Author:Sheldon RossPublisher:PEARSONA First Course in Probability (10th Edition)ProbabilityISBN:9780134753119Author:Sheldon RossPublisher:PEARSON