3. (10 pts.) X is a Gaussian random variable with E{X} = 2 and Var(X) =...
Let X be a continuous random variable with the following density function. Find E(X) and var(X). 6e -7x for x>0 f(x) = { for xso 6 E(X) = 49 var(X) =
Problem 1. Let X be a contiuous random variable with probability density 2T f0SS Let A be the event that X > 1/2. Compute EXA) and Var(XA).
1. Let X be a continuous random variable with probability density function f(x) = { if x > 2 otherwise 0 Check that f(-x) is indeed a probability density function. Find P(X > 5) and E[X]. 2. Let X be a continuous random variable with probability density function f(x) = = { SE otherwise where c is a constant. Find c, and E[X].
6. Let X be a normal random variable with mean u = 10. What is the standard deviation o if it is known that p (IX – 101 <>) =
The velocity of a particle in a gas is a random variable X with probability distribution fx(x) = 27 x2 -3x x >0. The kinetic energy of the particle is Y = {mXSuppose that the mass of the particle is 64 yg. Find the probability distribution of Y. (Do not convert any units.)
5. Let X ~ N(m, σ) be a scalar Gaussian random variable with mean m and arianx Compute its moment gencrating function EetX . Compute all the moments of X, i.e., E(X m)" for all integers p > 1.
Problem 2: Let X be a binomially distributed random variable based on n 10 trials with success probability p 0.3. a) Compute P(X 3 8), P(x-7 and PX> 6) by hand, showing your work.
Let random variable X follows an exponential distribution with probability density function fx (2) = 0.5 exp(-x/2), x > 0. Suppose that {X1, ..., X81} is i.i.d random sample from distribution of X. Approximate the probability of P(X1+...+X81 > 170). A. 0.67 B. 0.16 C. 0.33 D. 0.95 E. none of the preceding
3. (10 points) Let X be a continuous random variable with CDF for x < -1 Fx(x) = { } (x3 +1) for -1<x<1 for x > 1 and let Y = X5 a. (4 points) Find the CDF of Y. b. (3 points) Find the PDF of Y. c. (3 points) Find E[Y]
A random variable X has the following pdf, where is the parameter, f(x) = x>1. 2+1 Use the method of transformation to determine the pdf of Y = In X. Identify this distribution. X and Y are random variables with the following joint pdf, f(t,y) = e-(z+y), x >0, y>0. Find the joint probability density function of U and V by considering the transformation U x*y and V = Y. Hence, obtain the marginal density function of U