Another example of pseudocode: X-a random integer between 1 and 6 if X> 5 Y 1...
6. Suppose that X and Y are jointly continuous random variables with joint density f(r, y)otherwise (a) Given that X > 1, what is the expected value of Y? That is, calculate Ey X 〉 1).
Plz help me to do both quetions.
6. The continuous random variables X and Y have joint density 2e2)for and y 20 otherwise Find P(X >Y). (Answer: 3) 7. The continuous random variables X and Y have joint probability density function 10y for 01 and 0 yr fzy(z,y)=ï o otherwise Find the marginal density function fy(y). Show your work. Do not forget to indicate where the density is non-zero.
Let X, Y be two independent exponential random variables with means 1 and 3, respectively. Find P(X> Y)
Suppose that X is a continuous random variable whose probability density function is given by (C(4x sa f(x) - 0 otherwise a) What is the value of C? b) Find PX> 1)
Below is the p.d.f for the random variables X and Y, f(x,y)-36 0 otherwise Find the following probability Pr(x> 2) O 7/9 2/3 O 8/9
7. The random variables X and Y have joint probability density function f given by 1 for x > 0, |y| 0 otherwise. 1-x, Below you find a diagram highlighting the (r, y) pairs for which the pdf is 1 (a) Calculate the marginal probability density function fx of X (b) Calculate the marginal cumulative distribution function Fy of Y (c) Are X and Y independent? Explain.
7. The random variables X and Y have joint probability density function f given by 1 for x > 0, |y| 0 otherwise. 1-x, Below you find a diagram highlighting the (r, y) pairs for which the pdf is 1 (a) Calculate the marginal probability density function fx of X (b) Calculate the marginal cumulative distribution function Fy of Y (c) Are X and Y independent? Explain.
Let X and Y be a random variable with joint PDF: { ay fxy (x, y) x > 1,0 <y <1 0 otherwise x2, 1. What is a? 2. What is the conditional PDF fy\x(x|y) of Y given X = x? 3. What is the conditional expectation of Ygiven X? 4. What is the expected value of Y?
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.)
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].