Suppose that W, the amount of moisture in the air on a given day, is a gamma random variable with parameters ( t , β ) . That is, its density is f ( ω ) = β e − β ω ( β ω ) t − 1 Γ ( t ) , ω > 0 . Suppose also that given that W = ω . the number of accidents during that day—call it N—has a Poisson distribution with mean ω . Show that the conditional distribution of W given that N = n is the gamma distribution with parameters ( t + n , β + 1 ) .
Suppose that W, the amount of moisture in the air on a given day, is a gamma random variable with parameters ( t , β ) . That is, its density is f ( ω ) = β e − β ω ( β ω ) t − 1 Γ ( t ) , ω > 0 . Suppose also that given that W = ω . the number of accidents during that day—call it N—has a Poisson distribution with mean ω . Show that the conditional distribution of W given that N = n is the gamma distribution with parameters ( t + n , β + 1 ) .
Suppose that W, the amount of moisture in the air on a given day, is a gamma random variable with parameters
(
t
,
β
)
. That is, its density is
f
(
ω
)
=
β
e
−
β
ω
(
β
ω
)
t
−
1
Γ
(
t
)
,
ω
>
0
. Suppose also that given that
W
=
ω
. the number of accidents during that day—call it N—has a Poisson distribution with mean
ω
. Show that the conditional distribution of
W given that
N
=
n
is the gamma distribution with parameters
(
t
+
n
,
β
+
1
)
.
4. (i) Let a discrete sample space be given by
N = {W1, W2, W3, W4},
and let a probability measure P on be given by
P(w1) = 0.2, P(w2) = 0.2, P(w3) = 0.5, P(wa) = 0.1.
Consider the random variables X1, X2 → R defined by
X₁(w1) = 1, X₁(w2) = 2,
X2(w1) = 2, X2 (w2) = 2,
Find the joint distribution of X1, X2.
(ii)
X1(W3) = 1, X₁(w4) = 1,
X2(W3) = 1, X2(w4) = 2.
[4 Marks]
Let Y, Z be random variables on a probability space (, F, P).
Let the random vector (Y, Z) take on values in the set [0, 1] x [0,2] and let the
joint distribution of Y, Z on [0, 1] x [0,2] be given by
1
dPy,z (y, z) ==(y²z+yz2) dy dz.
harks 12 Find the distribution Py of the random variable Y.
[8 Marks]
marks 11
3
3/4 x 1/4
1.
There are 4 balls in an urn, of which 3 balls are white and 1 ball is
black. You do the following:
draw a ball from the urn at random, note its colour, do not return the
ball to the urn;
draw a second ball, note its colour, return the ball to the urn;
finally draw a third ball and note its colour.
(i) Describe the corresponding discrete probability space
(Q, F, P).
[9 Marks]
(ii)
Consider the following event,
A: Among the first and the third balls, one ball is white, the other is black.
Write down A as a subset of the sample space and find its probability, P(A).
[2 Marks]
There are 4 balls in an urn, of which 3 balls are white and 1 ball isblack. You do the following:• draw a ball from the urn at random, note its colour, do not return theball to the urn;• draw a second ball, note its colour, return the ball to the urn;• finally draw a third ball and note its colour.(i) Describe the corresponding discrete probability space(Ω, F, P). [9 Marks](ii) Consider the following event,A: Among the first and the third balls, one ball is white, the other is black.Write down A as a subset of the sample space Ω and find its probability, P(A)
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