Consider n coins, each of which independently comes up heads with probability p. Suppose that n is large and p is small, and let λ = n p . Suppose that all n coins are tossed; if at least one comes up heads, the experiment ends; if not, we again toss all n coins, and so on. That is, we stop the first time that at least one of the n coins come up heads. Let X denote the total number of heads that appear. Which of the following reasonings concerned with approximating P { X = 1 } is correct (in all cases, y is a Poisson random variable with parameter λ ) a. Because the total number of heads that occur when all n coins are rolled is approximately a Poisson random variable with parameter P { X = 1 } ≈ P { Y = 1 } = λ e − λ b. Because the total number of heads that occur when all n coins are rolled is approximately a Poisson random variable with parameter λ , and because we stop only when this number is positive, P { X = 1 } ≈ P { Y = 1 | Y > 0 } = λ e − λ 1 − e − λ c. Because at least one coin comes up heads, X will equal I if none of the other n − 1 coins come up heads. Because the number of heads resulting from these n − 1 coins is approximately Poisson with mean ( n − 1 ) p ≈ λ , P { X = 1 } ≈ P { Y = 0 } = e − λ .
Consider n coins, each of which independently comes up heads with probability p. Suppose that n is large and p is small, and let λ = n p . Suppose that all n coins are tossed; if at least one comes up heads, the experiment ends; if not, we again toss all n coins, and so on. That is, we stop the first time that at least one of the n coins come up heads. Let X denote the total number of heads that appear. Which of the following reasonings concerned with approximating P { X = 1 } is correct (in all cases, y is a Poisson random variable with parameter λ ) a. Because the total number of heads that occur when all n coins are rolled is approximately a Poisson random variable with parameter P { X = 1 } ≈ P { Y = 1 } = λ e − λ b. Because the total number of heads that occur when all n coins are rolled is approximately a Poisson random variable with parameter λ , and because we stop only when this number is positive, P { X = 1 } ≈ P { Y = 1 | Y > 0 } = λ e − λ 1 − e − λ c. Because at least one coin comes up heads, X will equal I if none of the other n − 1 coins come up heads. Because the number of heads resulting from these n − 1 coins is approximately Poisson with mean ( n − 1 ) p ≈ λ , P { X = 1 } ≈ P { Y = 0 } = e − λ .
Solution Summary: The author explains that the option that is concerned with P(X=1) is in correct with the all cases.
Consider n coins, each of which independently comes up heads with probability p. Suppose that n is large and p is small, and let
λ
=
n
p
. Suppose that all n coins are tossed; if at least one comes up heads, the experiment ends; if not, we again toss all n coins, and so on. That is, we stop the first time that at least one of the n coins come up heads. Let X denote the total number of heads that appear. Which of the following reasonings concerned with approximating
P
{
X
=
1
}
is correct (in all cases, y is a Poisson random variable with parameter
λ
)
a. Because the total number of heads that occur when all n coins are rolled is approximately a Poisson random variable with parameter
P
{
X
=
1
}
≈
P
{
Y
=
1
}
=
λ
e
−
λ
b. Because the total number of heads that occur when all n coins are rolled is approximately a Poisson random variable with parameter
λ
, and because we stop only when this number is positive,
P
{
X
=
1
}
≈
P
{
Y
=
1
|
Y
>
0
}
=
λ
e
−
λ
1
−
e
−
λ
c. Because at least one coin comes up heads, X will equal I if none of the other
n
−
1
coins come up heads. Because the number of heads resulting from these
n
−
1
coins is approximately Poisson with mean
(
n
−
1
)
p
≈
λ
,
P
{
X
=
1
}
≈
P
{
Y
=
0
}
=
e
−
λ
.
QUESTION 18 - 1 POINT
Jessie is playing a dice game and bets $9 on her first roll. If a 10, 7, or 4 is rolled, she wins $9. This happens with a probability of . If an 8 or 2 is rolled, she loses her $9. This has a probability of J. If any other number is rolled, she does not win or lose, and the game continues. Find the expected value for Jessie on her first roll.
Round to the nearest cent if necessary. Do not round until the final calculation.
Provide your answer below:
5 of 5
(i) Let a discrete sample space be given by
Ω = {ω1, 2, 3, 4},
Total marks 12
and let a probability measure P on be given by
P(w1) 0.2, P(w2) = 0.2, P(w3) = 0.5, P(w4) = 0.1.
=
Consider the random variables X1, X2 → R defined by
X₁(w3) = 1, X₁(4) = 1,
X₁(w₁) = 1, X₁(w2) = 2,
X2(w1) = 2, X2(w2) = 2, X2(W3) = 1, X2(w4) = 2.
Find the joint distribution of X1, X2.
(ii)
[4 Marks]
Let Y, Z be random variables on a probability space (N, F, P).
Let the random vector (Y, Z) take on values in the set [0,1] × [0,2] and let the
joint distribution of Y, Z on [0,1] × [0,2] be given by
1
dPy,z(y, z)
(y²z + y²²) dy dz.
Find the distribution Py of the random variable Y.
[8 Marks]
Total marks 16
5.
Let (,,P) be a probability space and let X : → R be a random
variable whose probability density function is given by f(x) = }}|x|e¯|×| for
x Є R.
(i)
(ii)
Find the characteristic function of the random variable X.
[8 Marks]
Using the result of (i), calculate the first two moments of the
random variable X, i.e., E(X") for n = 1, 2.
(iii) What is the variance of X?
[6 Marks]
[2 Marks]
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