Exercise 2. Determine, moment of a continuous random variable described by the probability density function efficient (...
Let X be a continuous random variable with probability density function fx()o otherwise Find the probability density function of YX2 Let X be a continuous random variable with probability density function fx()o otherwise Find the probability density function of YX2
be a continuous random variable with probability density function 3. Let for 0 r 1 a, for 2 < < 4 0, elsew here 2 7 fx(x) = (a) Find a to make fx(x) an acceptable probability density function. (b) Determine the (cumulative) distribution function F(x) and draw its graph.
is a continuous random variable with the probability density function (x) = { 4x 0 <= x <= 1/2 { -4x + 4 1/2 <= x <= 1 What is the equation for the corresponding cumulative density function (cdf) C(x)? [Hint: Recall that CDF is defined as C(x) = P(X<=x).] We were unable to transcribe this imageWe were unable to transcribe this imageProblem 2. (1 point) X is a continuous random variable with the probability density function -4x+41/2sxs1 What is...
Q 2. The probability density function of the continuous random variable X is given by Shell, -<< 0. elsewhere. f(x) = {&e*, -40<3<20 (a) Derive the moment generating function of the continuous random variable X. (b) Use the moment generating function in (a) to find the mean and variance of X.
Suppose that X is continuous random variable with 2. 1 € [0, 1] probability density function fx(2) = . Compute the 10 ¢ [0, 1]" following: (a) The expectation E[X]. (b) The variance Var[X]. (c) The cumulative distribution function Fx.
5. (Expected value) Let X be a continuous random variable with probability density function S2/a2 if 1 2, f(x) elsehwere. 0 Find the expected value E (In X). Hint: Integration by parts
Let X be a continuous random variable with values in [ 0, 1], uniform density function fX(x) ≡ 1 and moment generating function g(t) = (e t − 1)/t. Find in terms of g(t) the moment generating function for (a) −X. (b) 1 + X. (c) 3X. (d) aX + b.
7. A random process may be modeled as a random variable with the probability density function fx(x) fx(x) fx(x) x < 1/2 x 1 /2 = 2-4x = 4x-2 = 0 (a) Show that Jdfx(r)dr = 1 (b) Find the CDF, Fx() (c) Find the probability that X is between 1/3 and 2/3. (d) Find the expected value of X. (e) Find the mode of X (f) Find the median of X. (g) Find the variance of X and the...
1. Let X be a continuous random variable with the probability density function fx(x) = 0 35x57, zero elsewhere. Let Y be a Uniform (3, 7) random variable. Suppose that X and Y are independent. Find the probability distribution of W = X+Y.
5. Find the moment generating function of the continuous random variable X whose a. probability density is given by )-3 or 36 0 elsewhere find the values of μ and σ2. b, Let X have an exponential distribution with a mean of θ = 15 . Compute a. 6. P(10 < X <20); b. P(X>20), c. P(X>30X > 10), the variance and the moment generating function of x. d.