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Question:In example 3.5.10 verify that X and Y have the same Marginal pdf and that

\({f_1}\left( x \right) = \left\{ \begin{array}{l}2k{x^2}\frac{{{{\left( {1 - {x^2}} \right)}^{\frac{2}{3}}}}}{3} for - 1 \le x \le 1\\0 \,\,\,\,\,\,\,\,\,\,\,\,\,\,otherwise\end{array} \right.\) .

Short Answer

Expert verified

.X and Y have the same marginal pdf

Step by step solution

01

Given Information

The joint pdf of X and Y is

\(f\left( {x,y} \right) = \left\{ \begin{array}{l}k{x^2}{y^2}\,\,for\,{x^2} + {y^2} \le 1\\0\,\,\,\,\,\,\,\,\,\,\,\,\,otherwise\end{array} \right.\)

02

Computing the probability

As each point inside the circle can\({x^2} + {y^2} \le 1,\,\,f\left( {x,y} \right)\)can be factored.

This factorisation cannot be satisfied at every point outside this circle.

This shows X and Y are not independent.

As the joint pdf of X and Y is

\(f\left( {x,y} \right) = \left\{ \begin{array}{l}k{x^2}{y^2}\,\,for\,{x^2} + {y^2} \le 1\\0\,\,\,\,\,\,\,\,\,\,\,\,\,otherwise\end{array} \right.\)

The Marginal pdf of\(X,f\left( x \right)\)

\(\begin{array}{c}X,f\left( x \right) = \int\limits_{ - 1}^1 {K{x^2}{y^2}dy} \\ = 2k{x^2}\frac{{{{\left( {1 - {x^2}} \right)}^{\frac{3}{2}}}}}{3}\end{array}\)

Therefore,

\({f_1}\left( x \right) = \left\{ \begin{array}{l}2k{x^2}\frac{{{{\left( {1 - {x^2}} \right)}^{\frac{3}{2}}}}}{3}\,\,\,\,\,if - 1 \le x \le 1\\0\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,otherwise\end{array} \right.\)

Similarly the marginal density of\(Y,f\left( y \right)\)

\(\begin{array}{c}Y,f\left( y \right) = \int\limits_{ - 1}^1 {k{x^2}{y^2}dx} \\ = 2k{y^2}\frac{{{{\left( {1 - {y^2}} \right)}^{\frac{3}{2}}}}}{3}\end{array}\)

Therefore,

\({f_1}\left( y \right) = \left\{ \begin{array}{l}2k{y^2}\frac{{{{\left( {1 - {y^2}} \right)}^{\frac{3}{2}}}}}{3}\,\,\,\,\,\,\,\,\, - 1 \le y \le 1\\0\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,otherwise\end{array} \right.\)

Hence we can say that X and Y are not independent and have the same marginal pdf’s

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Most popular questions from this chapter

For the conditions of Exercise 1, find the p.d.f. of the

average \(\frac{{\left( {{{\bf{X}}_{\bf{1}}}{\bf{ + }}{{\bf{X}}_{\bf{2}}}} \right)}}{{\bf{2}}}\)

Suppose that\({X_1}...{X_n}\)are independent. Let\(k < n\)and let\({i_1}.....{i_k}\)be distinct integers between 1 and n. Prove that \(X{i_1}.....X{i_k}\)they are independent.

Suppose that the joint p.d.f. of two random variables X and Y is as follows:

\(f\left( {x,y} \right) = \left\{ \begin{aligned}{l}c\left( {x + {y^2}} \right)\,\,\,\,\,\,for\,0 \le x \le 1\,and\,0 \le y \le 1\\0\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,otherwise\end{aligned} \right.\)

Determine

(a) the conditional p.d.f. of X for every given value of Y, and

(b) \({\rm P}\left( {X > \frac{1}{2}|Y = \frac{3}{2}} \right)\).

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)\({\rm P}\left( {X > \frac{1}{2}|Y = \frac{3}{4}} \right)\)

Question:Suppose that a point (X,Y) is to be chosen from the squareSin thexy-plane containing all points (x,y) such that 0≤x≤1 and 0≤y≤1. Suppose that the probability that the chosen point will be the corner(0,0)is 0.1, the probability that it will be the corner(1,0)is 0.2, and the probability that it will be the corner(0,1)is 0.4, and the probability that it will be the corner(1,1)is 0.1. Suppose also that if the chosen point is not one of the four corners of the square, then it will be an interior point of the square and will be chosen according to a constant p.d.f. over the interior of the square. Determine

\(\begin{array}{l}\left( {\bf{a}} \right)\;{\bf{Pr}}\left( {{\bf{X}} \le \frac{{\bf{1}}}{{\bf{4}}}} \right)\;{\bf{and}}\\\left( {\bf{b}} \right)\;{\bf{Pr}}\left( {{\bf{X + Y}} \le {\bf{1}}} \right)\end{array}\)

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