Please answer #2. The example is a similar problem for reference.
Please answer #2. The example is a similar problem for reference. 2) (24pts) A uniformly distributed...
Problem # 8. a) Let X be a continuous random variable with known CDF FX(x). LetY = g(X) where g(·) is the so-called signum function, which extracts the sign of its argument. In other words, g(X) = { -1 x<0, 0 x=0, 1 x>0 } Express the PDF fY (y) in terms of the known CDF FX(x). b) Let X be a random variable with PDF: fX(x) = { x/2 0 <= x < 2, 0 otherwise} Let Y be...
For a random variable X with cumulative distribution function (cdf) Fx(x) = 1- (2/x)^2 ,x>2. (a).Find the pdf fX(x). (b).Consider the random variable Y = X^2. Find the pdf of Y, fY (y).
Let X be a random variable with PDF fx(X). Let Y be a random variable where Y=2|X|. Find the PDF of Y, fy(y) if X is uniformly distributed in the interval [−1, 2]
You only need to do Q2 (a)'s (i) and (ii). No need to do part
B
2. (a) Let X be a random variable with a continuous distribution F. (i) Show that the Random Variable Y = F(X) is uniformly distributed over (0,1). (Hint: Al- though F is the distribution of X, regard it simply as a function satisfying certain properties required to make it a CDF ! (ii) Now, given that Y = y, a random variable Z is...
Assume random variable ? is uniformly distributed in the
interval (−?/2 ,?⁄ 2]. Define the random variable ?=tan (?), where
tan (∙) denotes the tangent function. Note that the derivative of
tan (?) is 1/(cos (?)2) .
a) Find the PDF of ?.
b) Find the mean of ?
.Define the random variable ?=1/?.
c) Find the PDF of ?.
Assume random variable X is uniformly distributed in the interval (-1/2, 1/2). Define the random variable Y = tan(X), where...
2. Suppose X and Y are independent continuous random variables. Show that P(Y < X) = | Fy(x) · fx (x) dx -oo where Fy is the CDF of Y and fx is the PDF of X [hint: P[Y E A] = S.P(Y E A|X = x) · fx(x) dx]. Rewrite the above equation as an expectation of a function of X, i.e. P(Y < X) = Ex[•]. Use the above relation to compute P[Y < X] if X~Exp (2)...
Let X be a continuous random variable with PDF fx(x)- 0 otherwise We know that given Xx, the random variable Y is uniformly distributed on [-x,x. 1. Find the joint PDF fx(x, y) 2. Find fyo). 3. Find P(IYI <x3)
Let X be a continuous random variable with PDF fx(x)- 0 otherwise We know that given Xx, the random variable Y is uniformly distributed on [-x,x. 1. Find the joint PDF fx(x, y) 2. Find fyo). 3. Find P(IYI
1. Suppose that X and Y are random variables that can only take values in the intervals 0 X 2 and 0 Y 3 2. Suppose also that the joint cumulative distribution function (cdf) of X and Y, for 0 < 2 and 03 y 3 2, is as follows: Fy). 16 [5] (a) Determine the marginal cdf Fx(x) of X and the marginal cdf Fy () of Y [5] (b) Determine the joint probability density function (pdf) f(x, y)...
1. Let U be a random variable that is uniformly distributed on the interval (0,1) (a) Show that V 1 - U is also a uniformly distributed random variable on the interval (0,1) (b) Show that X-In(U) is an exponential random variable and find its associated parameter (c) Let W be another random variable that is uformly distributed on (0,1). Assume that U and W are independent. Show that a probability density function of Y-U+W is y, if y E...
Problem 3:
Problem 3: (20 points) Suppose X is a uniformly distributed continuous random variable over [1,3]. a. (10 points) If Y - 4X2, find f (y), the PDF of Y. Indicate the range for which it applies. b. (10 points) What is the expected value of Y 0 し( 4 4
Problem 3: (20 points) Suppose X is a uniformly distributed continuous random variable over [1,3]. a. (10 points) If Y - 4X2, find f (y), the PDF of...