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Introductory to Probability Models

Sheldon M. Ross

Chapter 5

The Exponential Distribution and the Poisson Process - all with Video Answers

Educators


Chapter Questions

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Problem 1

The time $T$ required to repair a machine is an exponentially distributed random variable with mean $\frac{1}{2}$ (hours).
(a) What is the probability that a repair time exceeds $\frac{1}{2}$ hour?
(b) What is the probability that a repair takes at least $12 \frac{1}{2}$ hours given that its duration exceeds 12 hours?

Jason Gerber
Jason Gerber
Numerade Educator
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Problem 2

Suppose that you arrive at a single-teller bank to find five other customers in the bank, one being served and the other four waiting in line. You join the end of the line. If the service times are all exponential with rate $\mu$, what is the expected amount of time you will spend in the bank?

Rashmi Sinha
Rashmi Sinha
Numerade Educator
01:15

Problem 3

Let $X$ be an exponential random variable. Without any computations, tell which one of the following is correct. Explain your answer.
(a) $E\left[X^{2} \mid X>1\right]=E\left[(X+1)^{2}\right]$
(b) $E\left[X^{2} \mid X>1\right]=E\left[X^{2}\right]+1$
(c) $E\left[X^{2} \mid X>1\right]=(1+E[X])^{2}$

Victor Salazar
Victor Salazar
Numerade Educator
01:52

Problem 4

Consider a post office with two clerks. Three people, $A, B$, and $C$, enter simultaneously. A and B go directly to the clerks, and $\mathrm{C}$ waits until either $\mathrm{A}$ or $\mathrm{B}$ leaves before he begins service. What is the probability that $\mathrm{A}$ is still in the post office after the other two have left when
(a) the service time for each clerk is exactly (nonrandom) ten minutes?
(b) the service times are $i$ with probability $\frac{1}{3}, i=1,2,3 ?$
(c) the service times are exponential with mean $1 / \mu$ ?

Dominador Tan
Dominador Tan
Numerade Educator
04:17

Problem 5

The lifetime of a radio is exponentially distributed with a mean of ten years. If Jones buys a ten-year-old radio, what is the probability that it will be working after an additional ten years?

Amany Waheeb
Amany Waheeb
Numerade Educator
03:11

Problem 6

In Example $5.3$ if server $i$ serves at an exponential rate $\lambda_{i}, i=1,2$, show that
$$
P\{\text { Smith is not last }\}=\left(\frac{\lambda_{1}}{\lambda_{1}+\lambda_{2}}\right)^{2}+\left(\frac{\lambda_{2}}{\lambda_{1}+\lambda_{2}}\right)^{2}
$$

Khoobchandra Agrawal
Khoobchandra Agrawal
Numerade Educator
04:06

Problem 7

If $X_{1}$ and $X_{2}$ are independent nonnegative continuous random variables, show that
$$
P\left\{X_{1}<X_{2} \mid \min \left(X_{1}, X_{2}\right)=t\right\}=\frac{r_{1}(t)}{r_{1}(t)+r_{2}(t)}
$$

Amany Waheeb
Amany Waheeb
Numerade Educator
01:04

Problem 8

$$
\text { If } X \text { has failure rate function } r(t), \text { show that } E[X]=E\left[\frac{1}{r(X)}\right] \text { . }
$$

Ma. Theresa  Alin
Ma. Theresa Alin
Numerade Educator
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Problem 9

Machine 1 is currently working. Machine 2 will be put in use at a time $t$ from now. If the lifetime of machine $i$ is exponential with rate $\lambda_{i}, i=1,2$, what is the probability that machine 1 is the first machine to fail?

Victor Salazar
Victor Salazar
Numerade Educator
03:00

Problem 10

Let $X$ and $Y$ be independent exponential random variables with respective rates $\lambda$ and $\mu$. Let $M=\min (X, Y)$. Find
(a) $E[M X \mid M=X]$
(b) $E[M X \mid M=Y]$
(c) $\operatorname{Cov}(X, M)$

Nick Johnson
Nick Johnson
Numerade Educator
03:00

Problem 11

Let $X, Y_{1, \ldots .}, Y_{n}$ be independent exponential rardom variables; $X$ having rate $\lambda_{1}$ and $Y_{i}$ having rate $\mu$. Let $A_{j}$ be the event that the $j$ th smallest of these $n+1$ random variables is one of the $Y_{i}$. Find $p=P\left\{X>\max _{i} Y_{i}\right\}$, by using the identity
$$
p=P\left(A_{1} \cdots A_{n}\right)=P\left(A_{1}\right) P\left(A_{2} \mid A_{1}\right) \cdots P\left(A_{n} \mid A_{l} \cdots A_{n-1}\right)
$$
Verify your answer when $n=2$ by conditioning on $X$ to obtain $p$.

Nick Johnson
Nick Johnson
Numerade Educator
03:56

Problem 12

If $X_{i}, i=1,2,3$, are independent exponential random variables with rates $\lambda_{i}, i=1,2,3$, find
(a) $P\left\{X_{1}<X_{2}<X_{3}\right\}$
(b) $P\left\{X_{1}<X_{2} \mid \max \left(X_{1}, X_{2}, X_{3}\right)=X_{3}\right\}$
(c) $E\left[\max X_{i} \mid X_{1}<X_{2}<X_{3}\right]$
(d) $E\left[\max X_{i}\right]$

Ekaveera Kumar
Ekaveera Kumar
Numerade Educator
04:52

Problem 13

Find, in Example $5.8$, the expected time until the $n$ th person on line leaves the line (either by entering service or departing without service).

Ahmad Reda
Ahmad Reda
Numerade Educator
01:53

Problem 14

Let $X$ be an exponential random variable with rate $\lambda$.
(a) Use the definition of conditional expectation to determine $E[X \mid X<c]$.
(b) Now determine $E[X \mid X<c]$ by using the following identity:
$$
E[X]=E[X \mid X<c] P\{X<c\}+E[X \mid X>c] P\{X>c\}
$$

Victor Salazar
Victor Salazar
Numerade Educator
01:07

Problem 15

In Example $5.3$, what is the expected time until all three customers have left the post office?

Prabhu Ramji
Prabhu Ramji
Numerade Educator
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Problem 16

Suppose in Example $5.3$ that the time it takes server $i$ to serve customers is exponentially distributed with mean $1 / \lambda_{i}, i=1,2$. What is the expected time until all three customers have left the post office?

Victor Salazar
Victor Salazar
Numerade Educator
01:38

Problem 17

A set of $n$ cities is to be connected via communication links. The cost to construct a link between cities $i$ and $j$ is $C_{i j}, i \neq j .$ Enough links should be constructed so that for each pair of cities there is a path of links that connects them. As a result, only $n-1$ links need be constructed. A minimal cost algorithm for
solving this problem (known as the minimal spanning tree problem) first constructs the cheapest of all the $\left(\begin{array}{l}n \\ 2\end{array}\right)$ links. Then, at each additional stage it chooses the cheapest link that connects a city without any links to one with links. That is, if the first link is between cities 1 and 2 , then the second link will either be between 1 and one of the links $3, \ldots, n$ or between 2 and one of the links $3, \ldots, n$. Suppose that all of the $\left(\begin{array}{l}n \\ 2\end{array}\right)$ costs $C_{i j}$ are independent exponential random variables with mean 1 . Find the expected cost of the preceding algorithm if
(a) $n=3$
(b) $n=4$

Victor Salazar
Victor Salazar
Numerade Educator
03:21

Problem 18

Let $X_{1}$ and $X_{2}$ be independent exponential random variables, each having rate $\mu$. Let
$$
X_{(1)}=\operatorname{minimum}\left(X_{1}, X_{2}\right) \quad \text { and } \quad X_{(2)}=\operatorname{maximum}\left(X_{1}, X_{2}\right)
$$
Find
(a) $\dot{E}\left[X_{(1)}\right]$
(b) $-\operatorname{Var}\left[X_{(1)}\right]$
(c) $E\left[\dot{X}_{(2)}\right]$
(d) $\operatorname{Var}\left[X_{(2)}\right]$

Amany Waheeb
Amany Waheeb
Numerade Educator
01:05

Problem 19

Repeat Exercise 18 , but this time suppose that the $X_{i}$ are independent exponentials with respective rates $\mu_{i}, i=1,2$

Sriram Soundarrajan
Sriram Soundarrajan
Numerade Educator
03:22

Problem 20

C?nsider a two-server system in which a customer is served first by server 1 . then by server 2 , and then depar?. The service times at server $i$ are exponential random variables with rates $\mu_{i}, i=1,2$. When you arrive, you find server 1 free and two customers at server 2 - customer $\mathrm{A}$ in service and customer B waiting in line.
(a) Find $P_{A}$, the probability that $A$ is still in service when you move over to server 2
(b) Find $P_{B}$, the probability that $B$ is still in the system when you move over to server $2 .$
(c) Find $E[T]$, where $T$ is the time that you spend in the system.
Hint: Write
$$
T=S_{\mathrm{I}}+S_{2}+W_{A}+W_{B}
$$
where $S_{i}$ is your service time at server $i, W_{A}$ is the amount of time you wait in queue while $A$ is being served, and $W_{B}$ is the amount of time you wait in queue while $B$ is being served.

Amany Waheeb
Amany Waheeb
Numerade Educator
03:27

Problem 21

In a certain system, a customer must first be served by server 1 and then by server 2 . The service times at server $i$ are exponential with rate $\mu_{i}, i=1,2$.
An arrival finding server 1 busy waits in line for that server. Upon completion of service at server.1, a customereitherenters service with server 2 if that server is free or else remains with server 1 (blocking any other customer from entering service) until server 2 is free. Customers depart the system after being served by server $2 .$ Suppose that when you arrive there is one customer in the system and that customer is being served by server 1 . What is the expected total time you spend in the system?

Stanley Enemuo
Stanley Enemuo
Numerade Educator
07:15

Problem 22

Suppose in Exercise 21 you arrive to find two others in the system, one being served by server 1 and one by server 2 . What is the expected time you spend in the system? Recall that if server 1 finishes before server 2, then server 1's customer will remain with him (thus blocking your entrance). until server 2 becomes free.

Chris Trentman
Chris Trentman
Numerade Educator
02:35

Problem 23

A flashlight needs two batteries to be operational. Consider such a flashlight along with a set of $n$ functional batteries-battery 1 , battery $2, \ldots$, battery $n$. Initially, battery 1 and 2 are installed. Whenever a battery fails, it is immediately replaced bythe lowest numbered functional battery that has not yet been put in use. Suppose that the lifetimes of the different batteries are independent exponential Trandom variables each having rate $\mu$. At a random time, call it $T$, a battery will fail andour stockpile will be empty. At that moment exactly one of the batteries - which we call battery $X$ -will not yet have failed.
(a). What is $P\{X=n\} ?$
(b) What is $P(X=1) ?$
(c) What is $P(X=i\} ?$
(d) Find $E[T]$.
(e) What is the distribution of $T ?$

Amany Waheeb
Amany Waheeb
Numerade Educator
02:30

Problem 24

The random variable whose probability density function is given by
$$
f(x)=\left\{\begin{array}{ll}
\frac{1}{2} \lambda e^{\lambda x}, & \text { if } x \leqslant 0 \\
\frac{1}{2} \lambda e^{-\lambda x}, & \text { if } x>0
\end{array}\right.
$$
is said to have a Laplace, sometimes called a double exponential, distribution.
(a) Verify that the preceding is a probability density function.
(b) Show that the distribution function of a Laplace random variable is
$$
F(x)=\left\{\begin{array}{ll}
\frac{1}{2} e^{\lambda x}, & \text { if } x \leqslant 0 \\
1-\frac{1}{2} e^{-\lambda x}, & \text { if } x>0
\end{array}\right.
$$
Let $X$ and $Y$ be independent exponential random variables with parameter $\lambda$. Also, let $I$ be independent of $X$ and $Y$ and let it be equally likely to be 1 or $-1$.
(c) Show that $X-Y$ is a Laplace random variable.
(d) Show that $I X$ is a Laplace random variable.
(e) Show that $W$ is a Laplace random variable, where
$$
W=\left\{\begin{array}{ll}
X, & \text { if } I=1 \\
-Y, & \text { if } I=-1
\end{array}\right.
$$

Khoobchandra Agrawal
Khoobchandra Agrawal
Numerade Educator
04:05

Problem 25

Customers can be served by any of three servers, where the service times of server $i$ are exponentially distributed with rate $\mu_{i}, i=1,2,3$. Whenever a server becomes free, the customer who has been waiting the longest begins service with that server.
(a) If you arrive to find all three servers busy and no one waiting, find the expected time until you depart the system.
(b) If you arrive to find all three servers busy and one person waiting, find the expected time until you depart the system.

Clarissa Noh
Clarissa Noh
Numerade Educator
04:05

Problem 26

Each entering customer must be served first by server 1 , then by server 2, and finally. by server 3 . The amount of time it takes to be served by server $i$ is an exponential random variable with rate $\mu_{i}, i=1,2,3$. Suppose you enter the system when it contains a single customer who is being served by server $3 .$
(a) Find the probability that server 3 will still be busy when you move over to server $2 .$
(b) Find the probability that server 3 will still be busy when you move over to server $3 .$
(c) Find the expected amount of time that you spend in the system. (Whenever you encounter a busy server, you must wait for the service in progress to end before you can enter service.)

Clarissa Noh
Clarissa Noh
Numerade Educator
01:39

Problem 27

In Exercise 26 , suppose that you enter the system when it contains a single customer who is being served by server 2 . Find the expected amount of time that you spend in the system.

Jacquelinne S. Mejia Sandoval
Jacquelinne S. Mejia Sandoval
Numerade Educator
01:31

Problem 28

Consider $n$ components with independent lifetimes which are such that component $i$ functions for an exponential time with rate $\lambda_{i} .$ Suppose that all components are initially in use and remain so until they fail.
(a) Find the probability that component 1 is the second component to fail.
(b) Find the expected time of the second failure.
Hint: Do not make use of part (a).

Hast Aggarwal
Hast Aggarwal
Numerade Educator
03:08

Problem 29

Two individuals, $A$ and $B$, both require kidney transplants. If she does not receive a new kidney, then $A$ will die after an exponential time with rate $\mu_{A}$, and $B$ after an exponential time with rate $\mu_{B}$. New kidneys arrive in accordance with a Poisson process having rate $\lambda$. It has been decided that the first kidney will go
to $A$ (or to $B$.if $B$ is alive and $A$ is not at that time) and the next one to $B$ (if still living).
(a) What is the probability that $A$ obtains a new kidney?
(b) What is the probability that $B$ obtains a new kidney?

Sheryl Ezze
Sheryl Ezze
Numerade Educator
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Problem 30

The lifetimes of 'A's dog and cat are independent exponential random variables with respective rates $\lambda_{d}$ and $\lambda_{c}$. One of them has just died. Find the expected additional lifetime of the other pet.

Rashmi Sinha
Rashmi Sinha
Numerade Educator
02:45

Problem 31

A doctor has scheduled two appointments, one at 1 P.M. and the other at $1: 30 \mathrm{P}, \mathrm{M}$. The amounts of time that appointments last are independent exponential random variables with mean 30 minutes. Assuming that both patients are on time, find the expected amount of time that the $1: 30$ appointment spends at the doctor's office.

Amany Waheeb
Amany Waheeb
Numerade Educator
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Problem 32

There are three jobs and a single worker who works first on job 1 , then on job 2 , and finally on job 3. The amounts of time that he spends on each job are independent exponential random variables with mean 1. Let $C_{i}$ be the time at which job $i$ is completed, $i=1,2,3$, and let $X=\sum_{i=1}^{3} C_{i}$ be the sum of these completion times. Find (a) $E[X]$, (b) $\operatorname{Var}(X)$.

Victor Salazar
Victor Salazar
Numerade Educator
03:00

Problem 33

Let $X$ and $Y$ be independent exponential random variables with respective rates $\lambda$ and $\mu$.
(a) Argue that, conditional on $X>Y$, the random variables $\min (X, Y)$ and $X-Y$ are independent.
(b) Use part (a) to conclude that for any positive constant $c$
$$
\begin{aligned}
E[\min (X, Y) \mid X>Y+c] &=E[\min (X, Y) \mid X>Y] \\
&=E[\min (X, Y)]=\frac{1}{\lambda+\mu}
\end{aligned}
$$
(c) Give a verbal explanation of why $\min (X, Y)$ and $X-Y$ are (unconditionally) independent.

Nick Johnson
Nick Johnson
Numerade Educator
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Problem 34

Let $X$ and $Y$ be independent exponential random variables with respective rates $\lambda$ and $\mu$, where $\lambda>\mu$. Let $c>0$.
(a) Show that the conditional density function of $X$, given that $X+Y=c$, is
$$
f_{X \mid X+Y}(x \mid c)=\frac{(\lambda-\mu) e^{-(\lambda-\mu) x}}{1-e^{-(\lambda-\mu x)}}, \quad 0<x<c
$$
(b) Use part (a) and the resuit of Exercise 14 to find $E[X \mid X+Y=c]$.
(c) Find $E[Y \mid X+Y=c]$.

Victor Salazar
Victor Salazar
Numerade Educator
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Problem 35

Show that Definition $5.1$ of a Poisson process implies Definition $5.3 .$

Rashmi Sinha
Rashmi Sinha
Numerade Educator
13:11

Problem 36

Let $S(t)$ denote the price of a security at time $t$. A popular model for the process $\{S(t), t \geqslant 0\}$ supposes that the price remains unchanged until a "shock" occurs, at which time the price is multiplied by a random factor. If we let $N(t)$ denote the number of shocks by time $t$, and let $X_{i}$ denote the $i^{\text {th }}$ multiplicative factor, then this model supposes that
$$
S(t)=S(0) \prod_{l=1}^{N(t)} X_{i}
$$
where $\prod_{l=1}^{N(t)} X_{i}$ i? equal to 1 when $N(t)=0$. Suppose that the $X_{l}$ are independent exponential random variables with rate $\mu$; that $\{N(t), t \geqslant 0\}$ is a Poisson process with rate $\lambda$; that $[N(t), t \geqslant 0\}$ is independent of the $X_{i}$; and that $S(0)=s$
(a) Find $E[S(t)]$
(b) Find $E\left[S^{2}(t)\right]$

Robin Corrigan
Robin Corrigan
Numerade Educator
02:02

Problem 37

Cars cr?s a certain point in the highway in accordance with a Poisson process with rate $\lambda=3$ per minute. If Reb blindly runs across the highway, then what is the probability that she will be uninjured if the amount of time that it takes her to cross the road is $s$ seconds? (Assume that if she is on the highway when a car passes by, then she will be injured.) Do it for $s=2,5,10,20$

Christopher Stanley
Christopher Stanley
Numerade Educator
02:02

Problem 38

Suppose in Exercise 37 that Reb is agile enough to escape from a single car, but if she encounters two or more 'oars while attempting to cross the road, then she will be injured. What is the probability that she will be unhurt if it takes her $s$ seconds to cross? Do it for $s=5,10,20,30$.

SL
Sohyun Lee
Numerade Educator
07:31

Problem 39

A certain scientific theory supposes that mistakes in cell division occur according to a Poisson process with rate $2.5$ per year, and that an individual dies when 196 such mistakes have occurred. Assuming this theory, find
(a) the mean lifetime of an individual,
(b) the variance of the lifetime of an individual.
Also approximate
(c) the probability that an individual dies before age $67.2$.
(d) the probability that an individual reaches age 90 .
(e) the probability that an individual reaches age 100 .

Robin Corrigan
Robin Corrigan
Numerade Educator
12:20

Problem 40

Show that if $\left\{N_{i}(t), t \geqslant 0\right\}$ are independent Poisson processes with rate $\lambda_{i}, i=1,2$, then $[N(t), t \geqslant 0\}$ is a Poisson process with rate $\lambda_{1}+\lambda_{2}$ where $N(t)=N_{\mathrm{I}}(t)+N_{2}(t)$

Robin Corrigan
Robin Corrigan
Numerade Educator
01:20

Problem 41

In Exercise 40 what is the probability that the first event of the combined process is from the $N_{1}$ process?

Yifan Xu
Yifan Xu
Numerade Educator
12:20

Problem 42

Let $\{N(t), t \geqslant 0]$ be a Poisson process. with rate $\lambda$. Let $S_{n}$ denote the time of the $n$ th event. Find
(a) $E\left[S_{4}\right]$
(b) $E\left[S_{4} \mid N(1)=2\right]$
(c) $E[N(4)-N(2) \mid N(1)=3]$

Robin Corrigan
Robin Corrigan
Numerade Educator
04:28

Problem 43

Customers arrive at a two-server service station according to a Poisson process with rate $\lambda$. Wheneyer a new customer arrives, any customer that is in the system inmediately departs. A new arrival enters service first with server 1 and then with server 2: If the service times at the servers are independent exponentials with respective rates $\mu_{1}$ and $\mu_{2}$, what proportion of entering customers completes their service with server $2 ?$

Mahnoor Khan
Mahnoor Khan
Numerade Educator
02:04

Problem 44

Cars pass 'a certain street location according to a Poisson process with ratee A woman who wants to cross the street at that location waits until she can see that no cars will come by in the next $T$ time units.
(a) Find the probability that her waiting time is $0 .$
(b) Find her expected waiting time.
Hint: Condition on the time of the first car.

Hast Aggarwal
Hast Aggarwal
Numerade Educator
01:29

Problem 45

Let $[N(t), t \geqslant 0\}$ be a Poisson process with rate $\lambda$, that is independent of the nonnegative random variable $T$ with mean $\mu$ and variance $\sigma^{2}$. Find
(a) $\operatorname{Cov}(T, N(T))$
(b) $\operatorname{Var}(N(T))$

Victor Salazar
Victor Salazar
Numerade Educator
01:29

Problem 46

Let $\{N(t), t \geqslant 0\}$ be a Poisson process with rate $\lambda$, that is independent of the sequence $X_{1}, X_{2}, \ldots$ of independent and identically distributed random variables with mean $\mu$ and variance $\sigma^{2}$. Find
$$
\operatorname{Cov}\left(N(t), \sum_{i=1}^{N(t)} X_{i}\right)
$$

Victor Salazar
Victor Salazar
Numerade Educator
03:22

Problem 47

Consider a two-server parallel queueing system where customers arrive according to a Poisson process with rate $\lambda$, and where the service times are exponential with rate $\mu$. Moreover, suppose that arrivals finding both servers busy immediately depart without receiving any service (such a customer is said to be lost), whereas those finding at least one free server immediately enter service and then depart when their service is completed.
(a) If both servers are presently busy, find the expected time until the next customer enters the system.
(b) Starting empty, find the expected time until both servers are busy.
(c) Find the expected time between two successive lost customers.

Amany Waheeb
Amany Waheeb
Numerade Educator
03:22

Problem 48

Consider an $n$ -server parallel queueing system where customers arrive according to a Poisson process with rate $\lambda$, where the service times are exponential random variables with rate $\mu$, and where any arrival finding all servers busy immediately departs without receiving any service. If an arrival finds all servers busy, find
(a) the expected number of busy servers found by the next arrival,
(b) the probability that the next arrival finds all servers free,
(c) the probability that the next arrival finds exactly $i$ of the servers free.

Amany Waheeb
Amany Waheeb
Numerade Educator
13:11

Problem 49

Events occur accórding to a Poisson process with rate $\lambda$. Each time an event occurs, we must decide whether or not to stop, with our objective being to stop at the last event to occur prior to some specified time $T$, where $T>1 / \lambda$. That is, if an event occurs at time $t, 0 \leqslant t \leqslant T$, and we decide to stop, then we win if there are no additional events by time $T$, and we lose otherwise. If we do not stop when an event occurs and no. additional events occur by time $T$, then we lose. Also, if no events occur by time $T$, then we lose. Consider the strategy that stops at the first event to occur after some fixed time $s, 0 \leqslant s \leqslant T$.
(a) Using this strategy, what is the probability of winning?
(b) What value of $s$ maximizes the probability of winning?
(c) Show that on?'s probability of winning when using the preceding strategy with the value of $s$ specified in part (b) is $1 / e$.

Robin Corrigan
Robin Corrigan
Numerade Educator
00:52

Problem 50

The number of hours between successive train arrivals at the station is uniformly distributed on $(0,1)$. Passengers arrive according to a Poisson process with rate 7 per hour. Suppose a train has just left the station. Let $X$ denote the number of people who get on the next train. Find
(a) $E[X]$
(b) $\operatorname{Var}(X)$

Hast Aggarwal
Hast Aggarwal
Numerade Educator
03:23

Problem 51

If an individual has never had'a previous automobile accident, then the probability he or she has an accident in the next $h$ time units is $\beta h+o(h) ;$ on the other hand, if he or she has ever had a previous accident, then the probability is $\alpha h+o(h)$. Find the expected number of accidents an individual has by time $t$.

Joshua Sieverding
Joshua Sieverding
Numerade Educator
03:43

Problem 52

Teams 1 and 2 are playing a match. The teams score points according to independent Poisson processes with respective rates $\bar{\lambda}_{1}$ and $\lambda_{2}$. If the match ends when one of the teams has scored $k$ more points than the other, find the probability that team 1 wins.
Hint: Relate this to the gambler's ruin problem.

Suman Saurav Thakur
Suman Saurav Thakur
Numerade Educator
04:00

Problem 53

The water level of a certain reservoir is depleted at a constant rate of 1000 units daily. The reservoir is refilled by randomly occurring rainfalls. Rainfalls occur according to a Poisson process with rate $.2$ per day. The amount of water added to the reservoir by a rainfall is 5000 units with probability $.8$ or 8000 units with probability .2. The present water level is just slightly below 5000 units.
(a) What is the probability the reservoir will be empty after five days?
(b) What is the probability the reservoir will be empty sometime within the next ten days?

James Kiss
James Kiss
Numerade Educator
08:11

Problem 54

A viral linear DNA molecule of length, say, 1 is often known to contain a certain "marked position," with the exact location of this mark being unknown. One approach to locating the marked position is to cut the molecule by agents that break it at points chosen according to a Poisson process with rate $\lambda$. It is then possible to determine the fragment that contains the marked position. For instance, letting $m$ denote the location on the line of the marked position, then if $L_{1}$ denotes the last Poisson event time before $m$ (or 0 if there are no Poisson events in $[0, m])$, and $R_{1}$ denotes the first Poisson event time after $m$ (or $I$ if there are no Poisson events in $[m, 1])$, then it would be learned that the marked position lies between $L_{1}$ and $R_{1} .$ Find
(a) $P\left\{L_{1}=0\right]$
(b) $P\left\{L_{1}<x\right\}, 0<x<m$
(c) $P\left[R_{1}=1\right\}$
(d) $P\left(R_{1}>x\right\}, m<x<1$
By repeating the preceding process on identical copies of the DNA molecule, we are able to zero in on the location of the marked position. If the cutting procedure is utilized on $n$ identical copies of the molecule, yielding the data $L_{i}, R_{i}, i=$ $1, \ldots, n$, then it follows that the marked position lies between $L$ and $R$, where
$$
L=\max _{i} L_{i}, \quad R=\min _{i} R_{i}
$$
(e) Find $E[R-L]$, and in doing so, show that $E[R-L] \sim \frac{2}{n \lambda}$.

Deborah Greenspan
Deborah Greenspan
Numerade Educator
04:04

Problem 55

Consider a single server queueing system where customers arrive according to a Poisson process with rate $\lambda$, service times are exponential with rate $\mu$, and customers are served in the order of their arrival. Suppose that a customer arrives and finds $n-1$ others in the system. Let $X$ denote the number in the system at the moment that customer departs. Find the probability mass function of $X$.
Hint: Relate this to a negative binomial random variable.

James Kiss
James Kiss
Numerade Educator
01:02

Problem 56

An event independently occurs on each day with probability $p$. Let $N(n)$ denote the total number of events that occur on the first $n$ days, and let $T_{r}$ denote the day on which the $r$ th event occurs.
(a) What is the distribution of $N(n) ?$
(b) What is the distribution of $T_{1} ?$
(c) What is the distribution of $T_{r} ?$
(d) Given that $N(n)=r$, show that the unordered set of $r$ days on which events occurred has the same distribution as a random selection (without replacement) of $r$ of the values $1,2, \ldots, n$.

Aman Gupta
Aman Gupta
Numerade Educator
03:32

Problem 57

Events occur according to a Poisson process with rate $\lambda=2$ per hour.
(a) What is the probability that no event occurs between 8 P.M. and 9 P.M.?
(b) Starting at noon, what is the expected time at which the fourth event occurs?
(c) What is the. probability that two or more events occur between $6 \mathrm{P.M}$. and 8 P.M.?

Mahnoor Khan
Mahnoor Khan
Numerade Educator
02:50

Problem 58

Pulses arrive at a Geiger counter in accordance with a Poisson process at a rate of three arrivals per minute. Each particle arriving at the counter has a probability $\frac{2}{3}$ of being recorded. Let $X(t)$ denote the number of pulses recorded by time $t$ minutes.
(a) $P[X(t)=0\}=?$
(b) $E[X(t)]=$ ?

Amany Waheeb
Amany Waheeb
Numerade Educator
07:13

Problem 59

There are two types of claims that are made to an insurance company. Let $N_{l}(t)$ denote the number of type $i$ claims made by time $t$, and suppose that $\left[N_{1}(t), t \geqslant 0\right\}$ and $\left\{N_{2}(t), t \geqslant 0\right]$ are independent Poisson processes with rates $\lambda_{1}=.10$ and $\lambda_{2}=1 .$ The amounts of successive type 1 claims are independent exponential random variables with mean $\$ 1000$ whereas the amounts from type 2 'claims are independ?nt exponential random variables with mean $\$ 5000$. A claim for $\$ 4000$ has just been received; what is the probability it is a type 1 claim?

Chris Trentman
Chris Trentman
Numerade Educator
04:28

Problem 60

Customers arrive at a bank at a Poisson rate $\lambda$. Suppose two customers arrived during the first hour. What is the probability that
(a) both arrived during the first 20 minutes?
(b) at least one arrived during the first 20 minutes?

Mahnoor Khan
Mahnoor Khan
Numerade Educator
01:56

Problem 61

A system has a random number of flaws that we will suppose is Poisson distributed with mean $c$. Each of these flaws will, independently, cause the system to fail at a random time having distribution $G$. When a system failure occurs, suppose that the flaw causing the failure is immediately located and fixed.
(a) What is the distribution of the number of failures by time $t$ ?
(b) What is the distribution of the number of flaws that remain in the system at time $t$ ?
(c) Are the random variables in parts (a) and (b) dependent or independent?

Hast Aggarwal
Hast Aggarwal
Numerade Educator
08:28

Problem 62

Suppose that the number of typographical errors in a new text is Poisson distributed with mean $\lambda$. Two proofreaders independently read the text. Suppose that each error is independently found by proofreader $i$ with probability $p_{i}, i=1,2$. Let $X_{1}$ denote the number of errors that are found by proofreader 1 but not by proofreader 2. Let $X_{2}$ denote the number of errors that are found by proofreader 2 but not by proofreader $1 .$ Let $X_{3}$ denote the number of errors that are found by both proofreaders. Finally, let $X_{4}$ denote the number of errors found by neither proofreader.
(a) Describe the joint probability distribution of $X_{1}, X_{2}, X_{3}, X_{4}$.
(b) Show that
$$
\frac{E\left[X_{1}\right]}{E\left[X_{3}\right]}=\frac{1-p_{2}}{p_{2}} \text { and } \frac{E\left[X_{2}\right]}{E\left[X_{3}\right]}=\frac{1-p_{1}}{p_{1}}
$$
Suppose now that $\lambda, p_{1}$, and $p_{2}$ are all unknown.
(c) By using $X_{i}$ as an estimator of $E\left[X_{i}\right], i=1,2,3$, present estimators of $p_{1}$, $p_{2}$, and $\lambda$.
(d) Give an estimator of $X_{4}$, the number of errors not found by either proofreader.

Chris Trentman
Chris Trentman
Numerade Educator
04:04

Problem 63

Consider an infinite server queueing system in which customers arrive in accordance with a Poisson process and where the service distribution is exponential with rate $\mu$. Let $X(t)$ denote the number of customers in the system at time $t$. Find
(a) $E[X(t+s) \mid X(s)=n]$
(b) $\operatorname{Var}[X(t+s) \mid X(s)=n]$
Hint: Divide the customers in the system at time $t+s$ into two groups, one consisting of "old" customers and the other of "new" customers.

James Kiss
James Kiss
Numerade Educator
04:04

Problem 64

Suppose that people arrive at a bus stop in accordance with a Poisson process with rate $\lambda$. The bus departs at time $t$. Let $X$ denote the total amount of waiting time of all those who get on the bus at time $t$. We want to determine $\operatorname{Var}(X)$. Let $N(t)$ denote the number of arrivals by time $t .$
(a) What is $E[X \mid N(t)] ?$
(b) Argue that $\operatorname{Var}[X \mid N(t)]=N(t) t^{2} / 12$
(c) What is $\operatorname{Var}(X) ?$

James Kiss
James Kiss
Numerade Educator
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Problem 65

An average of 500 people pass the California bar exam each year. A California lawyer practices law, on average, for 30 years. Assuming these numbers remain steady, how many lawyers would you expect California to have in $2050 ?$

Rashmi Sinha
Rashmi Sinha
Numerade Educator
01:39

Problem 66

Policyholders of a certain insurance company have accidents at times distributed according to a Poisson process with rate $\lambda$. The amount of time from when the accident occurs until a claim is made has distribution $G$.
(a) Find the probability there are exactly $n$ incurred but as yet unreported claims at time $t$.
(b) Suppose that each claim amount has distribution $F$, and that the claim amount is independent of the time that it takes to report the claim. Find the expected value of the sum of all incurred but as yet unreported claims at time $t .$

Manik Pulyani
Manik Pulyani
Numerade Educator
06:16

Problem 67

Satellites are launched into space at times distributed according to a Poisson process with rate $\lambda$. Each satellite independently spends a random time (having distribution $G$ ) in space before falling to the ground. Find the probability that none of the satellites in the air at time $t$ was launched before time $s$, where $s<t$.

Robin Corrigan
Robin Corrigan
Numerade Educator
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Problem 68

Suppose that electrical shocks having random amplitudes occur at times distributed according to a Poisson process $\{N(t), t \geqslant 0]$ with rate $\lambda$. Suppose that the amplitudes of the successive shocks are independent both of other amplitudes and of the arrival times of shocks, and also that the amplitudes have distribution $F$ with mean $\mu$. Suppose also that the amplitude of a shock decreases with time at an exponential 'rate $\alpha$, meaning that an initial amplitude $A$ will have value $A e^{-\alpha x}$ after an additional time $x$ has elapsed. Let $A(t)$ denote the sum of all amplitudes at time $t$. That is,
$$
A(t)=\sum_{i=1}^{N(t)} A_{i} e^{-\alpha\left(t-S_{i}\right)}
$$
where $A_{i}$ and $S_{l}$ are the initial amplitude and the arrival time of shock $i$.
(a) Find $E[A(t)]$ by conditioning an $N(t)$.
(b) Without any computations, explain why $A(t)$ has the same distribution as does $D(t)$ of Example $5.19 .$

Victor Salazar
Victor Salazar
Numerade Educator
02:15

Problem 69

For Example $5.19$, let $M(t)=E[D(t)]$
(a) Argue that
$$
M(t+h)=M(t)+e^{-\alpha t} M(h)
$$
(b) Argue that
$$
M(t+h)=M(h)+e^{-\alpha h} M(t)
$$
(c) Argue that
$$
M(h)=\lambda h \mu+\bar{o}(h)
$$
(d) Use parts (a) and (c) to derive and then solve a differential equation for $M(t)$.
(e) Use parts (b) and (c) to derive and then solve a differential equation for $M(t)$.

Ajay Singhal
Ajay Singhal
Numerade Educator
04:04

Problem 70

For the infinite server queue with Poisson arrivals and general service distribution $G$, find the probability that
(a) the first customer to arrive is also the first to depart. Let $S(t)$ equal the sum of the remainihg service times of all customers in the system at time $t$.
(b) Argue that $S(t)$ is a compound Poisson random variable.
(c) Find $E[S(t)]$.
(d) Find $\operatorname{Var}(S(t))$.

James Kiss
James Kiss
Numerade Educator
01:29

Problem 71

Let $S_{n}$ denote the time of the $n$ th event of the Poisson process $[N(t), t \geqslant 0\}$ having rate $\lambda$. Show, for an arbitrary function $g$, that the random variable $\sum_{i=1}^{N(t)} g\left(S_{i}\right)$ has the same distribution as the compound Poisson random variable $\sum_{i=1}^{N(t)} g\left(U_{i}\right)$, where $U_{1}, U_{2}, \ldots$ is a sequence of independent and identically distributed uniform $(0, t)$ random variables that is independent of $N$, a Poisson random variable with mean $\lambda t$. Consequently, conclude that
$$
E\left[\sum_{i=1}^{N(t)} g\left(S_{i}\right)\right]=\lambda \int_{0}^{t} g(x) d x \quad \operatorname{Var}\left(\sum_{i=1}^{N(t)} g\left(S_{i}\right)\right)=\lambda \int_{0}^{t} g^{2}(x) d x
$$

Victor Salazar
Victor Salazar
Numerade Educator
01:01

Problem 72

A cable car starts off with $n$ riders. The times between successive stops of the car are independent exponential random variables with rate $\lambda$. At each stop one rider gets off. This takes no time, and no additional riders get on. After a rider gets off the car, he or she walks home. Independently of all else, the walk takes an exponential time with rate $\mu$.
(a) What is the distribution of the time at which the last rider departs the car?
(b) Suppose the last rider departs the car at time $t$. What is the probability that all the other riders are home at that time?

Victor Salazar
Victor Salazar
Numerade Educator
01:29

Problem 73

Shocks occur according to a Poisson process with rate $\lambda$, and each shock independently causes a certain system to fail with probability $p$. Let $T$ denote the time at which the system fails and let $N$ denote the number of shocks that it takes.
(a) Find the conditional distribution of $T$ given that $N=n$.
(b) Calculate the conditional distribution of $N$, given that $T=t$, and notice that it is distributed as 1 plus a Poisson random variable with mean $\lambda(1-p) t$.
(c) Explain how the result in part (b) could have been obtained without any calculations.

Victor Salazar
Victor Salazar
Numerade Educator
01:28

Problem 74

The number of missing items in a certain location, call it $X$, is a Poisson random variable with mean $\lambda$. When searching the location, each item will independently be found after an exponentially distributed time with rate $\mu$. A reward of $R$ is received for each item found, and a searching cost of $C$ per unit of search time is incurred. Suppose that you search for a fixed time $t$ and then stop.
(a) Find your total expected return.
(b) Find the value of $t$ that maximizes the total expected return.
(c) The policy of searching for a fixed time is a static policy. Would a dynamic policy, which allows the decision as to whether to stop at each time $t$, depend on the number already found by $t$ be beneficial?
Hint: How does the distribution of the number of items not yet found by time $t$ depend on the number already found by that time?

Hunza Gilgit
Hunza Gilgit
Numerade Educator
06:56

Problem 75

Suppose that the times between successive arrivals of customers at a singleserver station are independent random variables having a common distribution $F$. Suppose that when a customer arrives, he or she either immediately enters service if the server is free or else joins the end of the waiting line if the server is busy with another customer. When the server completes work on a customer, that customer leaves the system and the next waiting customer, if there are any, enters service. Let $X_{n}$ denote the number of customers in the system immediately before the $n$ th arrival, and let $Y_{n}$ denote the number of customers that remain in the system when the $n$ th customêr departs. The successive service times of customers are independent random.variables (which are also independent of the interarrival times) having a common distribution $G$.
(a) If $F$ is the exponential distribution with rate $\lambda$, which, if any, of the processes $\left\{X_{n}\right\},\left\{Y_{n}\right]$ is a Markov chain?
(b) If $G$ is the exponential distribution with rate $\mu$, which, if any, of the processes $\left[X_{n}\right\},\left\{Y_{n}\right]$ is a Markov chain?
(c) Give the transition probabilities of any Markov chains in parts (a) and (b).

Robin Corrigan
Robin Corrigan
Numerade Educator
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Problem 76

For the model of Example $5.25$, find the mean and variance of the number of customers served in a busy period.

Rashmi Sinha
Rashmi Sinha
Numerade Educator
03:32

Problem 77

Events occur according to a nonhomogeneous Poisson process whose mean value function is given by
$$
m(t)=t^{2}+2 t, \quad t \geqslant 0
$$
What is the probability that $n$ events occur between times $t=4$ and $t=5 ?$

Mahnoor Khan
Mahnoor Khan
Numerade Educator
07:03

Problem 78

A store opens at 8 A.M. From 8 until 10 customers arrive at a Poisson rate of four an hour. Between 10 and 12 they arrive at a Poisson rate of eight an hour. From 12 to 2 the arrival rate increases steadily from eight per hour at 12 to ten per hour at 2; and from 2 to 5 the arrival rate drops steadily from ten per hour at 2 to four per hour at $5 .$ Determine the probability distribution of the number of customers that enter the store on a given day.

Robin Corrigan
Robin Corrigan
Numerade Educator
12:20

Problem 79

Consider a nonhomogeneous Poisson process whose intensity function $\lambda(t)$ is bounded and continuous. Show that such a process is equivalent to a process
of counted events from a (homogeneous) Poisson process having rate $\lambda$, where an event at time $t$ is counted (independent of the past) with probability $\lambda(t) / \lambda ;$ and where $\lambda$ is chosen so that $\lambda(s)<\lambda$ for all $s$.

Robin Corrigan
Robin Corrigan
Numerade Educator
06:16

Problem 80

Let $T_{1}, T_{2}, \ldots$ denote the interarrival times of events of a nonhomogeneous Poisson process having intensity function $\lambda(t)$.
(a) Are the $T_{i}$ independent?
(b) Are the $T_{t}$ identically distributed?
(c) Find the distribution of $T_{1}$.

Robin Corrigan
Robin Corrigan
Numerade Educator
01:29

Problem 81

(a) Let $\{N(t), t \geqslant 0]$ be a nonhomogeneous Poisson process with mean value function $m(t) .$ Given $N(t)=n$, show that the unordered set of arrival times has the same distribution as $n$ independent and identically distributed random variables having distribution function
$$
F(x)=\left\{\begin{array}{ll}
\frac{m(x)}{m(t)}, & x \leqslant t \\
1, & x \geqslant t
\end{array}\right.
$$
(b) Suppose that workmen incur accidents in accordance with a nonhomogeneous Poisson process with mean value function $m(t)$. Suppose further that each injured man is out of work for a random amount of time having distribution $F$. Let $X(t)$ be the number of workers who are out of work at time $t$. By using part
(a), find $E[X(t)]$.

Victor Salazar
Victor Salazar
Numerade Educator
06:16

Problem 82

Suppose that events occur according to a nonhomogeneous Poisson process with intensity function $\lambda(t), t \geqslant 0$. Suppose that, independently of anything that has previously occurred, an event at time $s$ will be counted with probability $p(s)$, $s \geqslant 0$. Let $N_{c}(t)$ denote the number of counted events by time $t .$
(a) What type of process is $\left\{N_{c}(t), t \geqslant 0\right\} ?$
(b) Prove your answer to part (a).

Robin Corrigan
Robin Corrigan
Numerade Educator
12:20

Problem 83

Suppose that $\left[N_{0}(t), t \geqslant 0\right\}$ is a Poisson process with rate $\lambda=1$. Let $\lambda(t)$ denote a nonnegative function of $t$, and let
$$
m(t)=\int_{0}^{t} \lambda(s) d s
$$
Define $N(t)$ by
$$
N(t)=N_{0}(m(t))
$$
Argue that $\{N(t), t \geqslant 0\}$ is a nonhomogeneous Poisson process with intensity function $\lambda(t), t \geqslant 0$

Robin Corrigan
Robin Corrigan
Numerade Educator
01:56

Problem 84

Let $X_{1}, X_{2}, \ldots$ be independent and identically distributed nonnegative continuous random variables having density function $f(x)$. We say that a record occurs at time $n$ if $X_{n}$ is larger than each of the previous values $X_{1}, \ldots, X_{n-1}$. (A record automatically occurs at time 1.) If a record occurs at time $n$, then $X_{n}$ is called a record value. In other words, a record occurs whenever a new high is reached, and that new high is called the record value. Let $N(t)$ denote the number of record values that are less than or equal to $t$. Characterize the process $\{N(t), t \geqslant 0]$ when
(a) $f$ is an arbitrary continuous density function.
(b) $f(x)=\lambda e^{-\lambda x}$
Hint: Finish the following sentence: There will be a record whose value is between $t$ and $t+d t$ if the first $X_{i}$ that is greater than $t$ lies between.....

Amany Waheeb
Amany Waheeb
Numerade Educator
01:14

Problem 85

An insurance company pays out claims on its life insurance policies in accordance with a Poisson process having rate $\lambda=5$ per week. If the amount of money paid on each policy is exponentially distributed with mean $\$ 2000$, what is the mean and variance of the amount of money paid by the insurance company in a four-week span?

FC
Frank Cai
Numerade Educator
01:17

Problem 86

In good years, storms occur according to a Poisson process with rate 3 per unit time, while in other years they occur according to a Poisson process with rate 5 per unit time. Suppose next year will be a good year with probability $0.3$. Let $N(t)$ denote the number of storms during the first $t$ time units of next year.
(a) Find $P\{N(t)=n\}$.
(b) Is $\{N(t)]$ a Poisson process?
(c) Does $[N(t)]$ have stationary increments? Why or why not?
(d) Does it have independent increments? Why or why not?
(e) If next year starts off with three storms by time $t=1$, what is the conditional probability it is a good year?

Sheryl Ezze
Sheryl Ezze
Numerade Educator
13:11

Problem 87

Determine
$$
\operatorname{Cov}[X(t), X(t+s)]
$$
when $\{X(t), t \geqslant 0]$ is a compound Poisson process.

Robin Corrigan
Robin Corrigan
Numerade Educator
04:23

Problem 88

Customers arrive at the automatic teller machine in accordance with a Poisson process with rate 12 per hour. The amount of money withdrawn on each transaction is a random variable with mean $\$ 30$ and standard deviation $\$ 50$. (A negative withdrawal means that money was deposited.) The machine is in use

Sonam Khatri
Sonam Khatri
Numerade Educator
07:28

Problem 89

Some components of a two-component system fail after receiving a shock. Shocks of three types arrive independently and in accordance with Poisson processes. Shocks of the first type arrive at a Poisson rate $\lambda_{1}$ and cause the first component to fail. Those of the second type arrive at a Poisson rate $\lambda_{2}$ and cause the second component to fail. The third type of shock arrives at a Poisson rate $\lambda_{3}$ and causes both components to fail. Let $X_{1}$ and $X_{2}$ denote the survival times for the two components. Show that the joint distribution of $X_{1}$ and $X_{2}$ is given by
$$
P\left\{X_{1}>s, X_{1}>t\right]=\exp \left\{-\lambda_{1} s-\lambda_{2} t-\lambda_{3} \max (s, t)\right\}
$$
This distribution is known as the bivariate exponential distribution.

Robin Corrigan
Robin Corrigan
Numerade Educator
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Problem 90

In Exercise 89 show that $X_{1}$ and $X_{2}$ both have exponential distributions.

Victor Salazar
Victor Salazar
Numerade Educator
02:36

Problem 91

Let $X_{1}, X_{2}, \ldots, X_{n}$ be independent and identically distributed exponential random variables. Show that the probability that the largest of them is greater than the sum of the others is $n / 2^{n-1}$. That is, if
$$
M=\max _{j} X_{j}
$$
then show
$$
P\left\{M>\sum_{i=1}^{n} X_{i}-M\right\}=\frac{n}{2^{n-1}}
$$
Hint: What is $P\left[X_{1}>\sum_{i=2}^{n} X_{i}\right\} ?$

Amany Waheeb
Amany Waheeb
Numerade Educator
00:26

Problem 92

Prove Equation (5.22).

Vikash Ranjan
Vikash Ranjan
Numerade Educator
02:30

Problem 93

Prove that
(a) $\max \left(X_{1}, X_{2}\right)=X_{1}+X_{2}-\min \left(X_{1}, X_{2}\right)$ and, in general,
$$
\text { (b) } \begin{aligned}
\max \left(X_{1}, \ldots, X_{n}\right)=& \sum_{1}^{n} X_{i}-\sum_{i<j} \min \left(X_{i}, X_{j}\right) \\
&+\sum_{i<j<k} \sum_{i} \min \left(X_{i}, X_{j}, X_{k}\right)+\cdots \\
&+(-1)^{n-1} \min \left(X_{i}, X_{j}, \ldots, X_{n}\right)
\end{aligned}
$$
Show by defining appropriate random variables $X_{i}, i=1, \ldots, n$, and by taking expectations in part (b) how to obtain the well-known formula
$$
P\left(\bigcup_{1}^{n} A_{l}\right)=\sum_{i} P\left(A_{i}\right)-\sum_{i<j} \sum\left(A_{i} A_{j}\right)+\cdots+(-1)^{n-1} P\left(A_{1} \cdots A_{n}\right)
$$

Subham Jyoti Mishra
Subham Jyoti Mishra
Numerade Educator
10:06

Problem 94

A two-dimensional Poisson process is a process of randomly occurring events in the plane such that
(i) for any region of area $A$ the number of events in that region has a Poisson distribution with mean $\lambda A$ and
(ii) the number of events in nonoverlapping regions are independent.
For such a process, consider an arbitrary point in the plane and let $X$ denote its distance from its nearest event (where distance is measured in the usual Euclidean manner). Show that
(a) $P\{X>t\}=e^{-\lambda \pi t^{2}}$
(b) $E[X]=\frac{1}{2 \sqrt{\lambda}}$

Mengchun Cai
Mengchun Cai
Numerade Educator
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Problem 95

Show, ir Example 5.7, that the distributions of the total cost are the same for the two algorithms.

Sarah Parrigin
Sarah Parrigin
Numerade Educator
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Problem 96

For the conditional Poisson process of Section 5.4.3, let $m_{1}=E[L], m_{2}=$ $E\left[L^{2}\right] .$ In terms of $m_{1}$ and $m_{2}$, find $\operatorname{Cov}(N(s), N(t))$ for $s \leqslant t .$

Victor Salazar
Victor Salazar
Numerade Educator