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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.

Short Answer

Expert verified

The probabilities are:

ℙ(X=1∣Y)=3955,ℙ(X=2∣Y)=311,ℙ(X=3∣Y)=155

Step by step solution

01

Step 1:Given information

Let Xbe the winnings of a gambler. Letp(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

02

Step 2:Explanation

Let Xbe a winning of the gambler. Also let us define p(i)=â„™(X=i)and suppose that p(0)=13,p(1)=p(-1)=1355,p(2)=p(-2)=111,p(3)=p(-3)=1165We are to calculate conditional probability of gambler winnning i=1,2,3given that he wins positive amount.

Firstly let us calculate the probability that he won a positive amount.

â„™(Y)=p(1)+p(2)+p(3)=1355+111+1165=55165=13

Therefore we have:

ℙ(X=1∣Y)=ℙ(X=1,Y)ℙ(Y)=ℙ(X=1)ℙ(Y)=135513=3955

ℙ(X=2∣Y)=ℙ(X=2,Y)ℙ(Y)=ℙ(X=2)ℙ(Y)=11113=311

ℙ(X=3∣Y)=ℙ(X=3,Y)ℙ(Y)=ℙ(X=3)ℙ(Y)=116513=155

Therefore, we are done.

03

Step 3:Final answer

The probabilities are

ℙ(X=1∣Y)=3955,ℙ(X=2∣Y)=311,ℙ(X=3∣Y)=155

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Most popular questions from this chapter

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.

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.

Suppose that Xtakes on one of the values0,1and2. If for some constantc,P{X=i}=cP{X=i-1},i=1,2, findE[X].

Suppose that the number of events that occur in a specified time is a Poisson random variable with parameter λ. If each event is counted with probability p, independently of every other event, show that the number of events that are counted is a Poisson random variable with parameter λp. Also, give an intuitive argument as to why this should be so. As an application of the preceding result, suppose that the number of distinct uranium deposits in a given area is a Poisson random variable with parameter λ=10. If, in a fixed period of time, each deposit is discovered independently with probability 150, find the probability that

(a) exactly ,

(b) at least 1, and

(c) at most 1deposit is discovered during that time.

Repeat Example 1Cwhen the balls are selected with replacement.

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