Question

The joint probability density function for two continuous random variables is: f(y1,y2) = k(y1^2 + y2)...

The joint probability density function for two continuous random variables is:
f(y1,y2) = k(y1^2 + y2)
for 0 <= y2 <= 1-y1^2

Find the value of the constant k so that this makes f(y1,y2) a valid joint probability density function.

Also compute (integration) P(Y2 >= Y1 + 1)

Homework Answers

Answer #1

For to be a valid joint pdf, the following condition must hold:

Substituting the values in the above condition:

Know the answer?
Your Answer:

Post as a guest

Your Name:

What's your source?

Earn Coins

Coins can be redeemed for fabulous gifts.

Not the answer you're looking for?
Ask your own homework help question
Similar Questions
if 2 random variables have a joint density f(y1, y2) = 6/5. * (y1 + y2^2)...
if 2 random variables have a joint density f(y1, y2) = 6/5. * (y1 + y2^2) What is an expression for f(y1|y2) for 0<y2<1 and then for f(y1| y2 =0.25)? Find E(Y1| Y2 = 0.25)
f(y1,y2)=k(1−y2), 0≤y1≤y2≤1.joint probability density function: a) Find P(Y1≤0.35|Y2=0.3) b) Find E[Y1|Y2=y2]. c) Find E[Y1|Y2=0.3]
f(y1,y2)=k(1−y2), 0≤y1≤y2≤1.joint probability density function: a) Find P(Y1≤0.35|Y2=0.3) b) Find E[Y1|Y2=y2]. c) Find E[Y1|Y2=0.3]
Let X and Y be two continuous random variables with joint probability density function f(x,y) =...
Let X and Y be two continuous random variables with joint probability density function f(x,y) = 6x 0<y<1, 0<x<y, 0 otherwise. a) Find the marginal density of Y . b) Are X and Y independent? c) Find the conditional density of X given Y = 1 /2
Let X and Y be two continuous random variables with joint probability density function ?(?, ?)...
Let X and Y be two continuous random variables with joint probability density function ?(?, ?) = { ? 2 + ?? 3 0 ≤ ? ≤ 1, 0 ≤ ? ≤ 2 0 ??ℎ?????? Find ?(? + ? ≥ 1). Sketch the surface in the ? − ? plane.
Let X and Y be two continuous random variables with joint probability density function f(x,y) =...
Let X and Y be two continuous random variables with joint probability density function f(x,y) = xe^−x(y+1), 0 , 0< x < ∞,0 < y < ∞ otherwise (a) Are X and Y independent or not? Why? (b) Find the conditional density function of Y given X = 1.(
A joint density function of the continuous random variables x and y is a function f(x,...
A joint density function of the continuous random variables x and y is a function f(x, y) satisfying the following properties. f(x, y) ≥ 0 for all (x, y) ∞ −∞ ∞ f(x, y) dA = 1 −∞ P[(x, y)  R] =    R f(x, y) dA Show that the function is a joint density function and find the required probability. f(x, y) = 1 8 ,   0 ≤ x ≤ 1, 1 ≤ y ≤ 9 0,   elsewhere P(0 ≤...
Let X and Y be jointly continuous random variables with joint density function f(x, y) =...
Let X and Y be jointly continuous random variables with joint density function f(x, y) = c(y^2 − x^2 )e^(−2y) , −y ≤ x ≤ y, 0 < y < ∞. (a) Find c so that f is a density function. (b) Find the marginal densities of X and Y . (c) Find the expected value of X
For continuous random variables X and Y with joint probability density function. f(x,y) = xe−(x+y) when...
For continuous random variables X and Y with joint probability density function. f(x,y) = xe−(x+y) when x > 0 and y > 0 f(x,y) = 0 otherwise a. Find the conditional density F xly (xly) b. Find the marginal probability density function fX (x) c. Find the marginal probability density function fY (y). d. Explain if X and Y are independent
) Suppose Y1 and Y2 are random variables of the discrete type which have the joint...
) Suppose Y1 and Y2 are random variables of the discrete type which have the joint pmf p(y1, y2) = (y1 + 2y2)/18,(y1, y2) = (1, 1),(1, 2),(2, 1),(2, 2), zero elsewhere. Compute E(3Y1 − 2Y2) and P(Y1 = 1|Y2 > 1) .
Suppose X and Y are continuous random variables with joint density function f(x,y) = x +...
Suppose X and Y are continuous random variables with joint density function f(x,y) = x + y for 0 ≤ x ≤ 1 and 0 ≤ y ≤ 1. (a). Compute the joint CDF F(x,y). (b). Compute the marginal density for X and Y . (c). Compute Cov(X,Y ). Are X and Y independent?