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Six individuals, including \({\rm{A}}\) and \({\rm{B}}\), take seats around a circular table in a completely random fashion. Suppose the seats are numbered\({\rm{1, \ldots ,6}}\). Let \({\rm{X = }}\) A's seat number and \({\rm{Y = B}}\) 's seat number. If A sends a written message around the table to \({\rm{B}}\) in the direction in which they are closest, how many individuals (including A and B) would you expect to handle the message?

Short Answer

Expert verified

The solution is \({\rm{E(g(X,Y)) = 2}}{\rm{.8}}\).

Step by step solution

01

Definition

Probability simply refers to the likelihood of something occurring. We may talk about the probabilities of particular outcomes—how likely they are—when we're unclear about the result of an event. Statistics is the study of occurrences guided by probability.

02

Determining the sample size

The

Expected Value

(mean value) of a random variable\({\rm{g(X,Y)}}\), where \({\rm{g( \times )}}\) is a function, denoted as \({\rm{E(g(X,Y))}}\)is given by

\({\rm{E(g(X,Y)) = }}\left\{ {\begin{aligned}{*{20}{l}}{\sum\limits_{\rm{x}} {\sum\limits_{\rm{y}} {\rm{g}} } {\rm{(x,y) \times p(x,y)}}}&{{\rm{,X and Y discrete }}}\\{\int_{{\rm{ - ¥}}}^{\rm{¥}} {\int_{{\rm{ - ¥}}}^{\rm{¥}} {\rm{g}} } {\rm{(x,y) \times f(x,y)dxdy}}}&{{\rm{,X and Y continuous}}{\rm{. }}}\end{aligned}} \right.\)

where \({\rm{p(x,y)}}\) is pmf and \({\rm{f(x,y)}}\) pdf.

We want to use this. In order to do that, we need to determine \({\rm{g(X,Y)}}\)which would be the number of individuals (including A and B) who handle the message.

We first need to notice that individuals \({\rm{A}}\) and \({\rm{B}}\)cannot sit on the same spot. The minimum number of individuals who can handle the message is two (only A and B), and that is if they sit one to another. The maximum number of people who can handle the message is \({\rm{4}}\) (if there are two people sitting from the left and right of \({\rm{A}}\) and \({\rm{B}}\) - they sit across).

The sits are numbered, \({\rm{X}}\)represent A's seat number, and \({\rm{Y}}\) represents B's seat number, therefore, \({\rm{(2,1)}}\)would mean that person A sits on seat\({\rm{2}}\), and person B sits on seat\({\rm{1}}\), and \({\rm{g(2,1)}}\) would be \({\rm{2}}\) , because the only two individuals who handles the message are \({\rm{A}}\) and\({\rm{B}}\). We will do the same thing and represent it in a table.

To compute the expectation, we need\({\rm{p(x,y)}}\). There are

\({\rm{6 \times 5 = 30}}\)

total number of ways that \({\rm{A}}\) and \({\rm{B}}\) can sit, therefore

\({\rm{p(x,y) = }}\frac{{\rm{1}}}{{{\rm{30}}}}{\rm{.}}\)

The following is true

\(\begin{aligned}{\rm{E(g(X,Y)) = }}\sum\limits_{\rm{x}} {\sum\limits_{\rm{y}} {\rm{g}} } {\rm{(x,y) \times p(x,y)}}\\{\rm{ = }}\frac{{\rm{1}}}{{{\rm{30}}}}{\rm{ \times }}\sum\limits_{\rm{x}} {\sum\limits_{\rm{y}} {\rm{g}} } {\rm{(x,y)}}\\{\rm{ = }}\frac{{\rm{1}}}{{{\rm{30}}}}{\rm{ \times 84}}\\{\rm{ = 2}}{\rm{.8}}\end{aligned}\)

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Most popular questions from this chapter

In an area having sandy soil,\({\rm{50}}\)small trees of a certain type were planted, and another \({\rm{50}}\) trees were planted in an area having clay soil. Let \({\rm{X = }}\) the number of trees planted in sandy soil that survive \({\rm{1}}\) year and \({\rm{Y = }}\)the number of trees planted in clay soil that survive \({\rm{1}}\) year. If the probability that a tree planted in sandy soil will survive \({\rm{1}}\)year is \({\rm{.7}}\)and the probability of \({\rm{1}}\)-year survival in clay soil is \({\rm{.6}}\), compute an approximation to \({\rm{P( - 5£ X - Y£ 5)}}\) (do not bother with the continuity correction).

Let \({\rm{X}}\) be the number of packages being mailed by a randomly selected customer at a certain shipping facility. Suppose the distribution of \({\rm{X}}\) is as follows:

a. Consider a random sample of size \({\rm{n = 2}}\) (two customers), and let \({\rm{\bar X}}\) be the sample mean number of packages shipped. Obtain the probability distribution of\({\rm{\bar X}}\).

b. Refer to part (a) and calculate\({\rm{P(\bar X\pounds2}}{\rm{.5)}}\).

c. Again consider a random sample of size\({\rm{n = 2}}\), but now focus on the statistic \({\rm{R = }}\) the sample range (difference between the largest and smallest values in the sample). Obtain the distribution of\({\rm{R}}\). (Hint: Calculate the value of \({\rm{R}}\) for each outcome and use the probabilities from part (a).)

d. If a random sample of size \({\rm{n = 4}}\) is selected, what is \({\rm{P(\bar X\pounds1}}{\rm{.5)}}\) ? (Hint: You should not have to list all possible outcomes, only those for which\({\rm{\bar x\pounds1}}{\rm{.5}}\).)

The number of parking tickets issued in a certain city on any given weekday has a Poisson distribution with parameter \({\rm{ \mu = 50}}\).

a. Calculate the approximate probability that between \({\rm{35 and 70 }}\)tickets are given out on a particular day.

b. Calculate the approximate probability that the total number of tickets given out during a \({\rm{5 - }}\)day week is between \({\rm{225 and 275}}\)

c. Use software to obtain the exact probabilities in (a) and (b) and compare to their approximations.

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b. Consider a random sample of \({\rm{16}}\) trucks. What is the probability that the sample mean processing time is between \({\rm{12}}\) and\({\rm{15\;min}}\)?

c. Why is the probability in (b) much larger than the probability in (a)?

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b. Calculate \({{\rm{\mu }}_{{{\rm{T}}_{\rm{o}}}}}\). How does it relate to \({\rm{\mu }}\), the population mean?

c. Calculate \({\rm{\sigma }}_{{{\rm{T}}_{\rm{o}}}}^{\rm{2}}\). How does it relate to \({{\rm{\sigma }}^{\rm{2}}}\), the population variance?

d. Let \({{\rm{X}}_{\rm{3}}}\) and \({{\rm{X}}_{\rm{4}}}\) be the number of lights at which a stop is required when driving to and from work on a second day assumed independent of the first day. With \({{\rm{T}}_{\rm{o}}}{\rm{ = }}\) the sum of all four \({{\rm{X}}_{\rm{i}}}\) 's, what now are the values of \({\rm{E}}\left( {{{\rm{T}}_{\rm{a}}}} \right)\) and \({\rm{V}}\left( {{{\rm{T}}_{\rm{a}}}} \right)\)?

e. Referring back to (d), what are the values of \({\rm{P}}\left( {{{\rm{T}}_{\rm{o}}}{\rm{ = 8}}} \right)\) and \(\text{P}\left( {{\text{T}}_{\text{e}}}\text{ }\!\!{}^\text{3}\!\!\text{ 7} \right)\) (Hint: Don't even think of listing all possible outcomes!)

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