Section 29

Conditional Expectation

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Problem 29.1

Let A\mathcal{A} be the algebra consisting of the two elements ∅\emptyset and the whole space Ω\Omega. Find E[ξ∣A]\mathbb {E}\left[\xi \mid \mathcal{A}\right].

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Problem 29.2

The joint distribution of a pair of integer-valued random variables ξ\xi and η\eta is given by the table

ξ=−1\xi = -1ξ=0\xi = 0ξ=1\xi = 1
η=−1\eta = -11/81/81/121/127/247/24
η=1\eta = 15/245/241/61/61/81/8

, where the entry at the intersection of column ξ=i\xi = i and row η=j\eta = j is the probability P(ξ=i,η=j)\mathbb {P}\left(\xi =i, \eta =j\right). Find:

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(a)

E[ξ∣η]\mathbb {E}\left[\xi \mid \eta \right];

(b)

E[η∣ξ]\mathbb {E}\left[\eta \mid \xi \right];

(c)

E[ξ∣η2]\mathbb {E}\left[\xi \mid \eta^{2}\right];

(d)

E[ξ∣η3]\mathbb {E}\left[\xi \mid \eta^{3}\right];

(e)

E[η∣ξ2]\mathbb {E}\left[\eta \mid \xi^{2}\right];

(f)

E[η∣ξ3]\mathbb {E}\left[\eta \mid \xi^{3}\right].

Problem 29.3

Solve problem 29.2 for the table

ξ=−2\xi = -2ξ=0\xi = 0ξ=1\xi = 1
η=−1\eta = -11/61/61/61/61/61/6
η=2\eta = 21/61/61/61/61/61/6
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(a)
(b)
(c)
(d)
(e)
(f)
Problem 29.4

Solve problem 29.2 for the table

ξ=−1\xi = -1ξ=0\xi = 0ξ=1\xi = 1
η=−2\eta = -21/81/81/121/127/247/24
η=0\eta = 01/121/121/121/121/81/8
η=1\eta = 11/81/81/121/1200
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(a)
(b)
(c)
(d)
(e)
(f)
Problem 29.5

On the probability space (Ω,F,P())(\Omega , \mathcal{F}, \mathbb {P}\left(\right)), where Ω=[0,1]\Omega = [0,1], F\mathcal{F} is the σ\sigma-algebra of Borel subsets, and P()\mathbb {P}\left(\right) is Lebesgue measure, a random variable ξ\xi is given. Let A\mathcal{A} be the σ\sigma-algebra generated by the sets [0,1/3)[0,1/3), {1/3}\{ 1/3\}, and (1/3,1/2)(1/3,1/2). Find E[ξ∣A]\mathbb {E}\left[\xi \mid \mathcal{A}\right] if:

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(a)

ξ(ω)=ω\xi (\omega ) = \omega;

(b)

ξ(ω)=sin⁡πω\xi (\omega ) = \sin \pi \omega;

(c)

ξ(ω)={1,ω∈[0,1/3],2,ω∈(1/3,1];\xi (\omega ) = \begin{cases} 1, & \omega \in [0, 1/3], \\ 2, & \omega \in (1/3, 1]; \end{cases}

(d)

ξ(ω)=1−ω\xi (\omega ) = 1 - \omega;

(e)

ξ(ω)=ω2\xi (\omega ) = \omega^{2};

(f)

ξ(ω)={0,ω∈[0,2/3],1,ω∈(2/3,1].\xi (\omega ) = \begin{cases} 0, & \omega \in [0, 2/3], \\ 1, & \omega \in (2/3, 1]. \end{cases}

Problem 29.6

On the probability space (Ω,F,P())(\Omega , \mathcal{F}, \mathbb {P}\left(\right)), where Ω=[0,1]\Omega = [0,1], F\mathcal{F} is the σ\sigma-algebra of Borel subsets, and P()\mathbb {P}\left(\right) is Lebesgue measure, a random variable ξ(ω)=ω\xi (\omega ) = \omega is given. Find E[ξ∣A]\mathbb {E}\left[\xi \mid \mathcal{A}\right] if A\mathcal{A} is the σ\sigma-algebra:

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(a)

of all Borel subsets of the segment [0,1][0,1] that are symmetric about the point 1/21/2;

(b)

generated by the sets [0,1/3][0,1/3] and [1/3,2/3][1/3,2/3];

(c)

generated by the random variable η=min⁡{2ω,1}\eta = \min \{ 2\omega , 1\}.

Problem 29.7

On the probability space (Ω,F,P())(\Omega , \mathcal{F}, \mathbb {P}\left(\right)), where Ω=[0,1]\Omega = [0,1], F\mathcal{F} is the σ\sigma-algebra of Borel subsets, and P()\mathbb {P}\left(\right) is Lebesgue measure, the random variables ξ(ω)=ω2\xi (\omega ) = \omega^{2} and

η(ω)={−1,ω<1/2,1,ω≥1/2 \eta (\omega ) = \begin{cases} -1, & \omega < 1/2, \\ 1, & \omega \geq 1/2 \end{cases}

are given. Sketch the graphs of:

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(a)

E[ξ∣η]\mathbb {E}\left[\xi \mid \eta \right];

(b)

E[ξ∣η2]\mathbb {E}\left[\xi \mid \eta^{2}\right].

Problem 29.8

Suppose the random variable ξ\xi takes at most nn values. Is it true that E[ξ∣A]\mathbb {E}\left[\xi \mid \mathcal{A}\right] also takes at most nn values?

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Problem 29.9

Must the random variable E[ξ∣A]\mathbb {E}\left[\xi \mid \mathcal{A}\right] be measurable with respect to σ(ξ)\sigma (\xi )?

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Problem 29.10

Let ξ\xi and η\eta be independent, identically distributed random variables with finite expectation. Find E[ξ∣ξ+η]\mathbb {E}\left[\xi \mid \xi +\eta \right].

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Problem 29.11

Is the following statement true: if ξn→ξ\xi_{n} \to \xi almost surely, then E[η∣ξn]→pE[η∣ξ]\mathbb {E}\left[\eta \mid \xi_{n}\right] \xrightarrow {p} \mathbb {E}\left[\eta \mid \xi \right] for every random variable η\eta?

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Problem 29.12

Let the random variable ξ\xi have the exponential distribution with parameter 11, and let t>0t>0. Find:

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(a)

E[ξ∣min⁡(ξ,t)]\mathbb {E}\left[\xi \mid \min (\xi ,t)\right];

(b)

E[ξ∣max⁡(ξ,t)]\mathbb {E}\left[\xi \mid \max (\xi ,t)\right].

Problem 29.13

Solve problem 29.12 if the random variable ξ\xi has the uniform distribution on the segment [0,2][0,2].

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(a)
(b)
Problem 29.14

Let the random variable ξ\xi have the standard normal distribution. Find E[ξ∣ξ2]\mathbb {E}\left[\xi \mid \xi^{2}\right].

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Problem 29.15

Let ξ\xi and η\eta be independent random variables, each with the standard normal distribution. Find E[ξ2+η2∣ξ+η]\mathbb {E}\left[\xi^{2}+\eta^{2} \mid \xi +\eta \right].

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Problem 29.16

Let the independent random variables ξ\xi and η\eta each have the geometric distribution with parameter pp. Find the conditional distribution P(ξ=k∣ξ+η=n)\mathbb {P}\left(\xi =k \mid \xi +\eta =n\right).

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Problem 29.17

Let the independent random variables ξ\xi and η\eta each have the Poisson distribution with parameter λ\lambda. Find:

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(a)

E[ξ2∣ξ+η=k]\mathbb {E}\left[\xi^{2} \mid \xi +\eta =k\right];

(b)

the conditional distribution P(ξ=k∣ξ+η=n)\mathbb {P}\left(\xi =k \mid \xi +\eta =n\right).

Problem 29.18

Let the random variables ξ\xi and η\eta be independent and have the binomial distribution with parameters mm and pp. Find:

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(a)

E[ξ2∣ξ+η=1]\mathbb {E}\left[\xi^{2} \mid \xi +\eta =1\right];

(b)

the conditional distribution P(ξ=k∣ξ+η=1)\mathbb {P}\left(\xi =k \mid \xi +\eta =1\right).

Problem 29.19

Let ξ1,…,ξn\xi_{1}, \ldots , \xi_{n} be independent random variables having the uniform distribution on the segment [0,1][0,1]. Find:

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(a)

E[ξ1∣max⁡(ξ1,…,ξn)]\mathbb {E}\left[\xi_{1} \mid \max (\xi_{1}, \ldots , \xi_{n})\right];

(b)

E[ξ1∣min⁡(ξ1,…,ξn)]\mathbb {E}\left[\xi_{1} \mid \min (\xi_{1}, \ldots , \xi_{n})\right].

Problem 29.20

Solve problem 29.19 if the random variables ξk\xi_{k} have the exponential distribution with parameter 11.

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Problem 29.21

Let ξ\xi and η\eta be independent random variables having the uniform distribution on the segment [0,1][0,1]. Find:

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(a)

E[ξ∣ξ+η]\mathbb {E}\left[\xi \mid \xi +\eta \right];

(b)

E[ξ−η∣ξ+η]\mathbb {E}\left[\xi -\eta \mid \xi +\eta \right];

(c)

E[ξ2−η2∣ξ+η]\mathbb {E}\left[\xi^{2}-\eta^{2} \mid \xi +\eta \right];

(d)

E[ξ+η∣ξ]\mathbb {E}\left[\xi +\eta \mid \xi \right].

Problem 29.22

Let E[ξ2]<∞\mathbb {E}\left[\xi^{2}\right] < \infty. Prove that the random variable ξ\xi is measurable with respect to the σ\sigma-algebra A\mathcal{A} if and only if

E[(ξ−E[ξ∣A])2]=0. \mathbb {E}\left[\left(\xi - \mathbb {E}\left[\xi \mid \mathcal{A}\right]\right)^{2}\right] = 0.
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Problem 29.23

Let E[ξ2]<∞\mathbb {E}\left[\xi^{2}\right] < \infty and E[η2]<∞\mathbb {E}\left[\eta^{2}\right] < \infty. Prove that if the equalities E[ξ∣η]=η\mathbb {E}\left[\xi \mid \eta \right] = \eta and E[η∣ξ]=ξ\mathbb {E}\left[\eta \mid \xi \right] = \xi hold, then ξ=η\xi = \eta almost surely.

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Problem 29.24

Find E[ξ∣η]\mathbb {E}\left[\xi \mid \eta \right] if the joint density of the random vector (ξ,η)(\xi ,\eta ) equals:

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(a)

p(x,y)={4xyfor 0≤x,y≤1,0otherwise;p(x,y) = \begin{cases} 4xy & \text{for } 0 \leq x,y \leq 1, \\ 0 & \text{otherwise}; \end{cases}

(b)

p(x,y)={x+yfor 0≤x,y≤1,0otherwise;p(x,y) = \begin{cases} x+y & \text{for } 0 \leq x,y \leq 1, \\ 0 & \text{otherwise}; \end{cases}

(c)

p(x,y)={ye−x+e−2xfor x≥0, 0≤y≤1,0otherwise;p(x,y) = \begin{cases} ye^{-x}+e^{-2x} & \text{for } x \geq 0,\ 0 \leq y \leq 1, \\ 0 & \text{otherwise}; \end{cases}

(d)

p(x,y)={1+9x2y28for −1≤x,y≤1,0otherwise;p(x,y) = \begin{cases} \dfrac {1+9x^{2}y^{2}}{8} & \text{for } -1 \leq x,y \leq 1, \\ 0 & \text{otherwise}; \end{cases}

(e)

the two-dimensional normal density with correlation coefficient ρ\rho.

Problem 29.25

Let the joint density of the random vector (ξ,η)(\xi ,\eta ) equal

p(x,y)={xe−x(y+1),x,y≥0,0,otherwise. p(x,y) = \begin{cases} xe^{-x(y+1)}, & x,y \geq 0, \\ 0, & \text{otherwise}. \end{cases}

Find:

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(a)

the one-dimensional (marginal) distributions of ξ\xi and η\eta;

(b)

the conditional density of ξ\xi given η\eta;

(c)

the conditional density of η\eta given ξ\xi;

(d)

the conditional mean E[ξ∣η]\mathbb {E}\left[\xi \mid \eta \right];

(e)

the conditional mean E[η∣ξ]\mathbb {E}\left[\eta \mid \xi \right].

Problem 29.26

Let ξ\xi have the Poisson distribution with parameter λ\lambda, and let the random variable E[η∣ξ]\mathbb {E}\left[\eta \mid \xi \right] have a normal density with zero mean and variance ξ\xi.

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(a)

Find the characteristic function of η\eta.

(b)

Prove that the distribution of η\eta has no density.

(c)

Prove that η/λ\eta /\sqrt{\lambda } converges weakly, as λ→∞\lambda \to \infty, to the standard normal law.

Problem 29.27

Let the random variable ξ\xi have the exponential distribution with parameter 11, and let the random variable E[η∣ξ]\mathbb {E}\left[\eta \mid \xi \right] have the Poisson distribution with parameter ξ\xi. Find the distribution of the random variable η\eta.

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Problem 29.28

Let ξ1,ξ2,…\xi_{1}, \xi_{2}, \ldots be independent, identically distributed random variables with finite expectation, and let Sn=ξ1+…+ξnS_{n} = \xi_{1} + \ldots + \xi_{n}. Let An\mathcal{A}_{n} be the σ\sigma-algebra generated by the sums Sn,Sn+1,…S_{n}, S_{n+1}, \ldots. Prove that

E[ξ1∣An]=Snn. \mathbb {E}\left[\xi _{1} \mid \mathcal{A}_{n}\right] = \frac{S_{n}}{n}.
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