The random vector ( X , Y ) is said to be uniformly distributed over a region R in the plane if, for some constant c, its joint density is f ( x , y ) = { c if ( x , y ) ∈ R 0 otherwise a. Show that 1 c = area of regopm R . Suppose that ( X , Y ) is uniformly distributed over the square centered at (0, 0) and with sides of length 2. b. Show that X and Y are independent, with each being distributed uniformly over ( − 1 , 1 ) . c. What is the probability that ( X , Y ) lies in the circle of radius 1 centered at the origin? That is, find P { X 2 + Y 2 ≤ 1 } .
The random vector ( X , Y ) is said to be uniformly distributed over a region R in the plane if, for some constant c, its joint density is f ( x , y ) = { c if ( x , y ) ∈ R 0 otherwise a. Show that 1 c = area of regopm R . Suppose that ( X , Y ) is uniformly distributed over the square centered at (0, 0) and with sides of length 2. b. Show that X and Y are independent, with each being distributed uniformly over ( − 1 , 1 ) . c. What is the probability that ( X , Y ) lies in the circle of radius 1 centered at the origin? That is, find P { X 2 + Y 2 ≤ 1 } .
The random vector
(
X
,
Y
)
is said to be uniformly distributed over a region R in the plane if, for some constant c, its joint density is
f
(
x
,
y
)
=
{
c
if
(
x
,
y
)
∈
R
0
otherwise
a. Show that
1
c
=
area of regopm R
. Suppose that
(
X
,
Y
)
is uniformly distributed over the square centered at (0, 0) and with sides of length 2.
b. Show that X and Y are independent, with each being distributed uniformly over
(
−
1
,
1
)
.
c. What is the probability that
(
X
,
Y
)
lies in the circle of radius 1 centered at the origin? That is, find
P
{
X
2
+
Y
2
≤
1
}
.
Quantities that have magnitude and direction but not position. Some examples of vectors are velocity, displacement, acceleration, and force. They are sometimes called Euclidean or spatial vectors.
Random variables X and Y are independent and distributed as Uniform(−1,3).Find the density of random vector (Z,W), say f(z,w), where Z and W are defined asZ = X + 2Y, W = 2X −Y.
Find the cdf and density of X2 where X ∼ N (μ, σ2).
Assuming that X and Y have joint distribution f(x,y) = cx for -x < y < x, 0 < x< 1, and f(x, y) = 0 otherwise. Find the density of W = X – Y
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