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Question:LetYbe the rate (calls per hour) at which calls arrive at a switchboard. LetXbe the number of calls during at wo-hour period. A popular choice of joint p.f./p.d.f. for(X, Y )in this example would be one like

\({\bf{f}}\left( {{\bf{x,y}}} \right){\bf{ = }}\left\{ \begin{array}{l}\frac{{{{\left( {{\bf{2y}}} \right)}^{\bf{x}}}}}{{{\bf{x!}}}}{{\bf{e}}^{{\bf{ - 3y}}}}\;{\bf{if}}\;{\bf{y > 0}}\;{\bf{and}}\;{\bf{x = 0,1, \ldots }}\\{\bf{0}}\;{\bf{otherwise}}\end{array} \right.\)

a. Verify thatfis a joint p.f./p.d.f. Hint:First, sum overthexvalues using the well-known formula for thepower series expansion of\({{\bf{e}}^{{\bf{2y}}}}\).

b. Find Pr(X=0).

Short Answer

Expert verified
  1. It is verified that f is a joint p.f/p.d.f.
  2. \(\Pr \left( {X = 0} \right) = \frac{1}{3}\)

Step by step solution

01

Given information

At a switchboard, the rate which is arriving a call per hour is Y and for a two-hour period, the number of calls is X.

The joint probability density function of (X,Y) is,

\(f\left( {x,y} \right) = \left\{ \begin{array}{l}\frac{{{{\left( {2y} \right)}^x}}}{{x!}}{e^{ - 3y}}\;if\;y > 0\;and\;x = 0,1, \ldots \\0\;otherwise\end{array} \right.\)

02

Determining the verification

a. .

To verify that f is a joint p.d.f or p.f and to verify its validity, we have to do the sum over all x values and integrate the sum over the region\({{\bf{S}}_{\bf{y}}}{\bf{ = }}\left\{ {{\bf{y:y > 0}}} \right\}\). Then we have to show that the value of the integration is 1.

So,

\(\begin{array}{c}\int\limits_0^\infty {\sum\limits_{x = 0}^\infty {{f_{X,Y}}\left( {x,y} \right)dy = } } \int\limits_0^\infty {\sum\limits_{x = 0}^\infty {\frac{{{{\left( {2y} \right)}^x}}}{{x!}}{e^{ - 3y}}dy} } \\ = \int\limits_0^\infty {{e^{ - 3y}}\sum\limits_{x = 0}^\infty {\frac{{{{\left( {2y} \right)}^x}}}{{x!}}dy} } \\ = \int\limits_0^\infty {{e^{ - 3y}}{e^{2y}}dy} \\ = \left. {{e^{ - y}}} \right|_0^\infty \\ = 1\end{array}\)[For the power series of\({e^{2y}}\)]

Thus, it is verified that f is joint p.d.f.

03

Calculating the probability

b.

The probability that X=0is-

\(\begin{array}{c}\Pr \left( {X = 0} \right) = {f_X}\left( 0 \right)\\ = \int\limits_0^\infty {{f_{X,Y}}\left( {0,y} \right)dy} \\ = \int\limits_0^\infty {\frac{{{{\left( {2y} \right)}^0}}}{{0!}}{e^{ - 3y}}dy} \\ = \int\limits_0^\infty {{e^{ - 3y}}dy} \\ = \left. {\frac{{{e^{ - 3y}}}}{3}} \right|_0^\infty \\ = \frac{1}{3}\end{array}\)

Thus, the probability is \(\frac{1}{3}\).

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Most popular questions from this chapter

Let Y be the rate (calls per hour) at which calls arrive at a switchboard. Let X be the number of calls during a two-hour period. Suppose that the marginal p.d.f. of Y is

\({{\bf{f}}_{\bf{2}}}\left( {\bf{y}} \right){\bf{ = }}\left\{ {\begin{align}{}{{{\bf{e}}^{{\bf{ - y}}}}}&{{\bf{if}}\,{\bf{y > 0,}}}\\{\bf{0}}&{{\bf{otherwise,}}}\end{align}} \right.\)

And that the conditional p.d.f. of X given\({\bf{Y = y}}\)is

\({{\bf{g}}_{\bf{1}}}\left( {{\bf{x}}\left| {\bf{y}} \right.} \right){\bf{ = }}\left\{ {\begin{align}{}{\frac{{{{\left( {{\bf{2y}}} \right)}^{\bf{x}}}}}{{{\bf{x!}}}}{{\bf{e}}^{{\bf{ - 2y}}}}}&{{\bf{if}}\,{\bf{x = 0,1,}}...{\bf{,}}}\\{\bf{0}}&{{\bf{otherwise}}{\bf{.}}}\end{align}} \right.\)

  1. Find the marginal p.d.f. of X. (You may use the formula\(\int_{\bf{0}}^\infty {{{\bf{y}}^{\bf{k}}}{{\bf{e}}^{{\bf{ - y}}}}{\bf{dy = k!}}} {\bf{.}}\))
  2. Find the conditional p.d.f.\({{\bf{g}}_{\bf{2}}}\left( {{\bf{y}}\left| {\bf{0}} \right.} \right)\)of Y given\({\bf{X = 0}}\).
  3. Find the conditional p.d.f.\({{\bf{g}}_{\bf{2}}}\left( {{\bf{y}}\left| 1 \right.} \right)\)of Y given\({\bf{X = 1}}\).
  4. For what values of y is\({{\bf{g}}_{\bf{2}}}\left( {{\bf{y}}\left| {\bf{1}} \right.} \right){\bf{ > }}{{\bf{g}}_{\bf{2}}}\left( {{\bf{y}}\left| {\bf{0}} \right.} \right)\)? Does this agree with the intuition that the more calls you see, the higher you should think the rate is?

Each student in a certain high school was classified according to her year in school (freshman, sophomore, junior, or senior) and according to the number of times that she had visited a certain museum (never, once, or more than once). The proportions of students in the various classifications are given in the following table:

Never once More than once

than once

Freshmen 0.08 0.10 0.04

Sophomores 0.04 0.10 0.04

Juniors 0.04 0.20 0.09

Seniors 0.02 0.15 0.10

a. If a student selected at random from the high school is a junior, what is the probability that she has never visited the museum?

b. If a student selected at random from the high school has visited the museum three times, what is the probability that she is a senior?

Suppose that three random variables X1, X2, and X3 have a continuous joint distribution with the following joint p.d.f.:

\({\bf{f}}\left( {{{\bf{x}}_{\bf{1}}}{\bf{,}}{{\bf{x}}_{\bf{2}}}{\bf{,}}{{\bf{x}}_{\bf{3}}}} \right){\bf{ = }}\left\{ {\begin{align}{}{{\bf{c}}\left( {{{\bf{x}}_{\bf{1}}}{\bf{ + 2}}{{\bf{x}}_{\bf{2}}}{\bf{ + 3}}{{\bf{x}}_{\bf{3}}}} \right)}&{{\bf{for0}} \le {{\bf{x}}_{\bf{i}}} \le {\bf{1}}\,\,\left( {{\bf{i = 1,2,3}}} \right)}\\{\bf{0}}&{{\bf{otherwise}}{\bf{.}}}\end{align}} \right.\)

Determine\(\left( {\bf{a}} \right)\)the value of the constant c;

\(\left( {\bf{b}} \right)\)the marginal joint p.d.f. of\({{\bf{X}}_{\bf{1}}}\)and\({{\bf{X}}_{\bf{3}}}\); and

\(\left( {\bf{c}} \right)\)\({\bf{Pr}}\left( {{{\bf{X}}_{\bf{3}}}{\bf{ < }}\frac{{\bf{1}}}{{\bf{2}}}\left| {{{\bf{X}}_{\bf{1}}}{\bf{ = }}\frac{{\bf{1}}}{{\bf{4}}}{\bf{,}}{{\bf{X}}_{\bf{2}}}{\bf{ = }}\frac{{\bf{3}}}{{\bf{4}}}} \right.} \right){\bf{.}}\)

Suppose that the p.d.f. of X is as follows:

\(\begin{aligned}f\left( x \right) &= e{}^{ - x},x > 0\\ &= 0,x \le 0\end{aligned}\)

Determine the p.d.f. of \({\bf{Y = }}{{\bf{X}}^{\frac{{\bf{1}}}{{\bf{2}}}}}\)

Suppose that\({X_1}....{X_n}\)are i.i.d. random variables, each having the following c.d.f.:\(F\left( x \right) = \left\{ \begin{array}{l}0\,\,\,\,\,\,\,\,\,\,\,\,\,\,for\,x \le 0\\1 - {e^{ - x}}\,\,\,for\,x > 0\end{array} \right.\)

Let\({Y_1} = min\left\{ {{X_1},{X_2}..{X_n}} \right\}\)and\({Y_n} = max\left\{ {{X_{1,}}{X_2}..{X_n}} \right\}\)Determine the conditional p.d.f. of\({Y_1}\)given that\({Y_n} = {y_n}\)

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