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In Example 5c, compute the variance of the length of time until the miner reaches safety.

Short Answer

Expert verified

The required variance is equal to value are218.

Step by step solution

01

Given Information

The variance of the length of time until the miner reaches safety.

02

Explanation

Let's calculate second moment using the similar idea in Example 5cWe have that,

EX2=EX2Y=1P(Y=1)+EX2Y=2P(Y=2)

+EX2Y=3P(Y=3)

Observe that,

EX2Y=1=9.

03

Explanation 

Since if he chooses the first door, the expected square of time needed to escape is equal to 9. Also, if he chooses the second door, he will need 5+Xof time to escape. Similarly if he chooses the third door.

Hence, EX2Y=2=E(X+5)2=EX2+10E(X)+25

EX2Y=3=E(X+7)2=EX2+14E(X)+49.

04

Explanation

Therefore, we end up with equation

EX2=139+EX2+10E(X)+25+EX2+14E(X)+49

Which yields,

EX2=83+24E(X)

Add the value,

=443

Because we know that E(X)=15.

The variance is equal to(X)=E(X2)-E(X)2

=218.

05

Final answer

The required variance is equal to value are218.

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Most popular questions from this chapter

Consider an urn containing a large number of coins, and suppose that each of the coins has some probability p of turning up heads when it is flipped. However, this value of pvaries from coin to coin. Suppose that the composition of the urn is such that if a coin is selected at random from it, then the p-value of the coin can be regarded as being the value of a random variable that is uniformly distributed over 0,1. If a coin is selected at random from the urn and flipped twice, compute the probability that

a. The first flip results in a head;

b. both flips result in heads.

In the text, we noted that

Ei=1Xi=i=1EXi

when the Xiare all nonnegative random variables. Since

an integral is a limit of sums, one might expect that E0X(t)dt=0E[X(t)]dt

whenever X(t),0t<,are all nonnegative random

variables; this result is indeed true. Use it to give another proof of the result that for a nonnegative random variable X,

E[X)=0P(X>t}dt

Hint: Define, for each nonnegative t, the random variable

X(t)by

role="math" localid="1647348183162" X(t)=1ift<X\\0iftX

Now relate4q

0X(t)dttoX

Suppose that the expected number of accidents per week at an industrial plant is 5. Suppose also that the numbers of workers injured in each accident are independent random variables with a common mean of 2.5. If the number of workers injured in each accident is independent of the number of accidents that occur, compute the expected number of workers injured in a week .

Let X be the length of the initial run in a random ordering of n ones and m zeros. That is, if the first k values are the same (either all ones or all zeros), then X Ú k. Find E[X].

Between two distinct methods for manufacturing certain goods, the quality of goods produced by method iis a continuous random variable having distribution Fi,i=1,2. Suppose that goods are produced by method 1 and mby method 2 . Rank the n+mgoods according to quality, and let

Xj=1    if thejth best was produced from    method12    otherwise

For the vector X1,X2,,Xn+m, which consists of n1'sand m2's, let Rdenote the number of runs of 1 . For instance, if n=5,m=2, and X=1,2,1,1,1,1,2, then R=2. If F1=F2(that is, if the two methods produce identically distributed goods), what are the mean and variance of R?

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