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Suppose that the random variables X and Y have the following joint p.d.f.:

\({\bf{f}}\left( {{\bf{x,y}}} \right){\bf{ = }}\left\{ {\begin{aligned}{{}{}}{{\bf{8xy}}}&{{\bf{for}}\,{\bf{0}} \le {\bf{x}} \le {\bf{y}} \le {\bf{1,}}}\\{\bf{0}}&{{\bf{otherwise}}{\bf{.}}}\end{aligned}} \right.\)

Also, let\({\bf{U = }}{\raise0.7ex\hbox{\({\bf{X}}\)} \!\mathord{\left/{\vphantom {{\bf{X}} {\bf{Y}}}}\right.}\!\lower0.7ex\hbox{\({\bf{Y}}\)}}\)and\({\bf{V = Y}}\).

a. Determine the joint p.d.f. of U and V .

b. Are X and Y independent?

c. Are U and V independent?

Short Answer

Expert verified

a. The joint p.d.f. of U and V is,

\(f\left( {u,v} \right) = \left\{ {\begin{aligned}{{}{}}{8u{v^3}}&{for\,0 \le u \le 1,\,\,0 \le v \le 1,}\\0&{otherwise,}\end{aligned}} \right.\)

b. X and Y are not independent.

c. U and V are independent.

Step by step solution

01

Given information

The joint p.d.f. of X and Y is,

\(f\left( {x,y} \right) = \left\{ {\begin{aligned}{{}{}}{8xy}&{for\,0 \le x \le y \le 1,}\\0&{otherwise.}\end{aligned}} \right.\)

02

Finding the joint probability density function of U and V

Let us consider the transformation

\(u = {\raise0.7ex\hbox{$x$} \!\mathord{\left/{\vphantom {x y}}\right.}\!\lower0.7ex\hbox{$y$}}\) and \(v = y\)

So,

\(x = uv\)and\(y = v\)

The Jacobian is,

\(\begin{aligned}{}J &= \left| {\frac{{\partial \left( {x,y} \right)}}{{\partial \left( {u,v} \right)}}} \right|\\ &= \left| {\begin{aligned}{*{20}{c}}{\frac{{\partial x}}{{\partial u}}}&{\frac{{\partial x}}{{\partial v}}}\\{\frac{{\partial y}}{{\partial u}}}&{\frac{{\partial y}}{{\partial v}}}\end{aligned}} \right|\\ &= \left| {\begin{aligned}{{}{}}v&u\\0&1\end{aligned}} \right|\\ &= \left( {v - 0} \right)\\ &= v\, > 0\end{aligned}\)

The joint p.d.f. of U and V is,

\(\begin{aligned}{}f\left( {u,v} \right) &= f\left( {uv,v} \right) \times J\\ &= 8uv \times v \times v\\ &= 8u{v^3}\end{aligned}\)

Therefore, the joint p.d.f. of U and V is,

\(f\left( {u,v} \right) = \left\{ {\begin{aligned}{{}{}}{8u{v^3}}&{for\,0 \le u \le 1,0 \le v \le 1,}\\0&{otherwise,}\end{aligned}} \right.\)

03

Checking whether of X and Y are independent.

The marginal pdf of X is

\(\begin{aligned}{}f\left( x \right) &= \int_x^1 {f\left( {x,y} \right)dy} \\ &= \int_x^1 {8xydy} \\ &= 8x\int_x^1 {ydy} \\ &= 8x\left( {\frac{{{y^2}}}{2}} \right)_x^1\\ &= 4x\left( {1 - {x^2}} \right)\end{aligned}\)

The marginal pdf of Y is

\(\begin{aligned}{}f\left( y \right) &= \int_0^y {f\left( {x,y} \right)dx} \\ &= \int_0^y {8xydx} \\ &= 8y\int_0^y {xdx} \\ &= 8y\left( {\frac{{{x^2}}}{2}} \right)_0^y\\ &= 4y\left( {{y^2}} \right)\\ &= 4{y^3}\end{aligned}\)

Here,\(f\left( {x,y} \right) \ne f\left( x \right) \times f\left( y \right)\).

X and Y are not independent.

04

Checking whether of U and V are independent.

The marginal p.d.f. U is,

\(\begin{aligned}{}f\left( u \right) &= \int_0^1 {f\left( {u,v} \right)dv} \\ &= \int_0^1 {8u{v^3}dv} \\ &= 8u\int_0^1 {{v^3}dv} \\ &= 8u\left( {\frac{{{v^4}}}{4}} \right)_0^1\\ &= \frac{{8u}}{4}\\ &= 2u\end{aligned}\)

The marginal p.d.f. V is,

\(\begin{aligned}{}f\left( v \right) &= \int_0^1 {f\left( {u,v} \right)du} \\ &= \int_0^1 {8u{v^3}du} \\ &= 8{v^3}\int_0^1 {udu} \\ &= 8{v^3}\left( {\frac{{{u^2}}}{2}} \right)_0^1\\ &= \frac{{8{v^3}}}{2}\\ &= 4{v^3}\end{aligned}\)

\(f\left( {u,v} \right) = f\left( u \right)f\left( v \right)\)

Therefore, U and V are independent

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Most popular questions from this chapter

Question:Suppose thatXandYhave a continuous joint distribution for which the joint p.d.f. is

\({\bf{f}}\left( {{\bf{x,y}}} \right){\bf{ = }}\left\{ \begin{array}{l}{\bf{k}}\;{\bf{for}}\;{\bf{a}} \le {\bf{x}} \le {\bf{b}}\;{\bf{and}}\;{\bf{c}} \le {\bf{y}} \le {\bf{d}}\\{\bf{0}}\;{\bf{otherwise}}\end{array} \right.\)

wherea <b,c < d, andk >0.

Find the marginal distributions ofXandY.

Start with the joint distribution of treatment group and response in Table 3.6 on page 138. For each treatment group, compute the conditional distribution of response given the treatment group. Do they appear to be very similar or quite different?

Suppose that the joint p.d.f. of two points X and Y chosen by the process described in Example 3.6.10 is as given by Eq. (3.6.15). Determine (a) the conditional p.d.f.of X for every given value of Y , and (b)\({\rm P}\left( {X > \frac{1}{2}|Y = \frac{3}{4}} \right)\)

Find the unique stationary distribution for the Markov chain in Exercise 2.

Question:Suppose that in a certain drug the concentration of aparticular chemical is a random variable with a continuousdistribution for which the p.d.f.gis as follows:

\({\bf{g}}\left( {\bf{x}} \right){\bf{ = }}\left\{ \begin{array}{l}\frac{{\bf{3}}}{{\bf{8}}}{{\bf{x}}^{\bf{2}}}\;{\bf{for}}\;{\bf{0}} \le {\bf{x}} \le {\bf{2}}\\{\bf{0}}\;{\bf{otherwise}}\end{array} \right.\)

Suppose that the concentrationsXandYof the chemicalin two separate batches of the drug are independent randomvariables for each of which the p.d.f. isg. Determine

(a) the joint p.d.f.of X andY;

(b) Pr(X=Y);

(c) Pr(X >Y );

(d) Pr(X+Y≤1).

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