Problem #9: The velocity of a particle in a gas is a random variable X with...
The velocity of a particle in a gas is a random variable X with probability distribution fx(x) = 27x2e-3x x >0. The kinetic energy of the particle is Y = mx?. Suppose that the mass of the particle is 64 yg. Find the probability distribution of Y. (Do not convert any units.)
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.)
The velocity of a particle in a gas is a random variable X with probability distribution fX (x) = 256 x^2 e^(−8x) x > 0. The kinetic energy of the particle is Y = (1/2 )* (mX^ 2). Suppose that the mass of the particle is 49 yg. Find the probability distribution of Y. (Do not convert any units.)
Problem #3: The velocity of a particle in a gas is a random variable X with probability distribution fx (x) = 343 z2 e-7x x>0. The kinetic energy of the particle is Y = 2 mx2. Suppose that the mass of the particle is 16 yg. Find the probability distribution of Y. (Do not convert any units.) Enter your answer as a symbolic 343/16*sqrt(2*y/16)*(e^(-7*sqrt(2*) function of y, as in these examples Problem #3: 343 V (e-71 (20)/16) + e7V (2/16))...
Problem 5. A particle of mass 1g has a random velocity X that is uniformly distributed between 3cm/s and 8cm/s. X2. (a) Find the cumulative distribution function of the particles kinetic energy T = (b) Find the probability density function of T. (c) Find the mean of T
Suppose that X is a continuous random variable with probability
distribution
Suppose that X is a continuous random variable with probability distribution O<x<6 18 (a) Find the probability distribution of the random variable Y-10X 3. fr o) 2 Edit for Sy s (b) Find the expected value of Y
Define the random variable Y = -2X. Determine the cumulative
distribution function (CDF) of Y . Make sure to completely specify
this function. Explain.
Consider a random variable X with the following probability density function (PDF): s 2+2 if –2 < x < 2, fx(x) = { 0 otherwise. This random variable X is used in parts a, b, and c of this problem.
2.5.6. The probability density function of a random variable X is given by f(x) 0, otherwise. (a) Find c (b) Find the distribution function Fx) (c) Compute P(l <X<3)
Let X be a continuous random variable with the following PDF 6x(1 – x) if 0 < x < 1 fx(x) = 3 0.w. Suppose that we know Y | X = x ~ Geometric(x). Find the posterior density of X given Y = 2, i.e., fxY (2|2).
Problem 5. Suppose that the continuous random variable X has the distribution fx(z),-oo < x < oo, which is symmetric about the value x-0. Evaluate the integral: Fx (t)dt -k where Fx(t) is the CDF for X, and k is a non-negative real number.