Let X be a random number from (0,1). Find the probability density functions of the random variables
be random number from . So it can be considered as uniform. We can write the density as
.
Let
When x=0, y=0 and when
So the density of Y is given by
which is the exponential density.
So has exponential distribution with probability density function
.
Now we want to find the density of
Whenx=0,z=0 and when x=1, z=1.
So the density of Z is given by
So the probability density function of Z is given by .
Let X be a random number from (0,1). Find the probability density functions of the random...
Let X ~ U[0,1] be a standard uniform random variable. Find the probability density functions (pdf's) of the following random variables: iii) Y = 1/x0.5
Let X and Y be continuous and independent random variables, both with uniform distribution (0,1). Find the functions of probability densities of (a) X + Y (b) X-Y (c) | X-Y |
Problem 4. Let X~N(0,1) and Ye. Find the probability density function of Y. This random variable Y is called a log-normal random variable and is frequently used in mathematical modeling of asset prices.
Let X and Y denote independent random variables with respective probability density functions, f(x) = 2x, 0<x<1 (zero otherwise), and g(y) = 3y2, 0<y<1 (zero otherwise). Let U = min(X,Y), and V = max(X,Y). Find the joint pdf of U and V.
Let X and Y be two random variables with the joint probability density function: f(x,y) = cxy, for 0 < x < 3 and 0 < y < x a) Determine the value of the constant c such that the expression above is valid. b) Find the marginal density functions for X and Y. c) Are X and Y independent random variables? d) Find E[X].
2) Two statistically-independent random variables, (X,Y), each have marginal probability density, N(0,1) (e.g., zero-mean, unit-variance Gaussian). Let V-3X-Y, Z = X-Y Find the covariance matrix of the vector, 2) Two statistically-independent random variables, (X,Y), each have marginal probability density, N(0,1) (e.g., zero-mean, unit-variance Gaussian). Let V-3X-Y, Z = X-Y Find the covariance matrix of the vector,
Let X, Y, Z be independent uniform random variables on [0,1]. What is the probability that Y lies between X and Z.
Let X and Y be independent Gaussian(0,1) random variables. Define the random variables R and Θ, by R2=X2+Y2,Θ = tan−1(Y/X).You can think of X and Y as the real and the imaginary part of a signal. Similarly, R2 is its power, Θ is the phase, and R is the magnitude of that signal. (a) Find the joint probability density function of R and Θ, i.e.,fR,Θ(r,θ).
Let the random variables X, Y with joint probability density function (pdf) fxy(z, y) = cry, where 0 < y < z < 2. (a) Find the value of c that makes fx.y (a, y) a valid pdf. (b) Calculate the marginal density functions for X and Y (c) Find the conditional density function of Y X (d) Calculate E(X) and EYIX) (e Show whether X. Y are independent or not.
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