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Suppose that the distribution function of X given by

F(b)=0 â¶Ä…â¶Ä…â¶Ä…b<0b4 â¶Ä…â¶Ä…â¶Ä…0≤b<112+b−14 â¶Ä…â¶Ä…â¶Ä…1≤b<21112 â¶Ä…â¶Ä…â¶Ä…2≤b<31 â¶Ä…â¶Ä…â¶Ä…3≤b

(a) Find P{X=i},i=1,2,3.

(b) Find P12<X<32.

Short Answer

Expert verified

(a) The value for the P{x=i} if i=1,2,3 are

P{1}=14

P{2}=16

P{3}=112

(b) The value for theP12<X<32is12.

Step by step solution

01

Given information (Part a)

The distribution function of X given as

F(b)=0 â¶Ä…â¶Ä…â¶Ä…b<0b4 â¶Ä…â¶Ä…â¶Ä…0≤b<112+b−14 â¶Ä…â¶Ä…â¶Ä…1≤b<21112 â¶Ä…â¶Ä…â¶Ä…2≤b<31 â¶Ä…â¶Ä…â¶Ä…3≤b

02

Solution (Part a)

The calculation is given below,

P(X=1)=F(1+)−F(1−)

=12+1−14−14

=14

P(X=2)=F(2+)−F(2−)

=1112−12−2−14

=1112−12−14

=11−6−312

=16

Similarly,

P(X=3)=1−1112

=112

03

Final answer (Part a)

The value for the P{x=i} if i=1,2,3 are

P{1}=14

P{2}=16

P{3}=112

04

Given information (Part b)

Given in the question that

F(b)=0 â¶Ä…â¶Ä…â¶Ä…b<0b4 â¶Ä…â¶Ä…â¶Ä…0≤b<112+b−14 â¶Ä…â¶Ä…â¶Ä…1≤b<21112 â¶Ä…â¶Ä…â¶Ä…2≤b<31 â¶Ä…â¶Ä…â¶Ä…3≤b

05

Solution (Part b)

The calculation is given below,

P12<X<32=F(3/2)−F(1/2)

=12+32−14−124

=12+12×14−12×14

=12

06

Final answer (Part b)

The value for theP12<X<32is12.

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Most popular questions from this chapter

A newsboy purchases papers at 10 cents and sells them at 15 cents. However, he is not allowed to return unsold papers. If his daily demand is a binomial random variable with n=10,p=13, approximately how many papers should he purchase so as to maximize his expected profit?

Suppose that a die is rolled twice. What are the possible values that the following random variables can take on:

(a) the maximum value to appear in the two rolls;

(b) the minimum value to appear in the two rolls;

(c) the sum of the two rolls;

(d) the value of the first roll minus the value of the second roll?

Let Xbe a negative binomial random variable with parameters rand p, and let Ybe a binomial random variable with parameters nand p. Show that

P{X>n}=P{Y<r}

Hint: Either one could attempt an analytical proof of the preceding equation, which is equivalent to proving the identity

∑i=n+1∞ i−1r−1pr(1−p)i−r=∑i=0r−1 ni×pi(1−p)ni

or one could attempt a proof that uses the probabilistic interpretation of these random variables. That is, in the latter case, start by considering a sequence of independent trials having a common probability p of success. Then try to express the events to express the events {X>n}and {Y<r}in terms of the outcomes of this sequence.

LetXbe the winnings of a gambler. Let p(i)=P(X=i)and suppose that

p(0)=1/3;p(1)=p(-1)=13/55

p(2)=p(-2)=1/11;p(3)=p(-3)=1/165

Compute the conditional probability that the gambler wins i,i=1,2,3,given that he wins a positive amount.

The random variable X is said to have the Yule-Simons distribution if

P{X=n}=4n(n+1)(n+2),n≥1

(a) Show that the preceding is actually a probability mass function. That is, show that∑n=1∞P{X=n}=1

(b) Show that E[X] = 2.

(c) Show that E[X2] = q

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