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Suppose that the p.d.f. of a random variable X is as

follows:\(f\left( x \right) = \left\{ \begin{array}{l}\frac{1}{2}x\,\,\,\,\,\,\,\,for\,0 < x < 2\\0\,\,\,\,\,\,\,\,\,\,\,\,otherwise\end{array} \right.\)

Also, suppose that \(Y = X\left( {2 - X} \right)\) Determine the cdf and the pdf of Y .

Short Answer

Expert verified

Cdf of Y is

\(G\left( y \right) = \left\{ \begin{array}{l}0\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,y < 2\\\frac{1}{{36}}\,\,\,\,\,\,\,\,\,\,\,\,z \le y < 8\\1\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,if\,y \ge 8\end{array} \right.\)

Pdf of Y is \(f\left( y \right) = \left\{ \begin{array}{l} = \frac{1}{{18}}\left( {y - 2} \right)\,\,if\,\,z \le y < 8\\\,\,0\,\,\,\,\,\,\,if\,y < 2\,\,or\,y \ge 8\,\,\end{array} \right.\)

Step by step solution

01

Calculating the CDF

First we have to find out the cdf of X

\(\begin{aligned}F\left( x \right) = \int\limits_{ - \infty }^x {f\left( z \right)dz} \\\left\{ \begin{aligned}if\,x < 0\,\,\,\,\,\,F\left( x \right) &= 0\\x \in \left[ {0,2} \right)\,\,\,\,\,F\left( x \right) &= \int\limits_{ - \infty }^x {F\left( z \right)dz} \\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, &= \int\limits_0^x {\frac{z}{2}dz} \\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, &= \left. {\frac{1}{2} \times \frac{{{z^2}}}{2}} \right|_0^x\\\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\, &= \frac{{{x^2}}}{4}\\x \ge 2\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,F\left( x \right) &= 1\end{aligned} \right.\end{aligned}\)

Finding cdf of Y using cdf of X

\(\begin{aligned}G\left( y \right) &= {\rm P}\left( {Y \le y} \right)\\ &= {\rm P}\left( {3x + 2 \le y} \right)\\ &= {\rm P}\left( {x \le \frac{1}{3}\left( {y - 2} \right)} \right)\end{aligned}\)

\(G\left( y \right) = F\left( {\frac{1}{3}\left( {y - 2} \right)} \right)\)

If \(\frac{1}{3}\left( {y - 2} \right) < 0\,\,or\,y < 2\,\, \Rightarrow G\left( y \right) = 0\,\,or\,y < 2\)

If \(0 \le \frac{1}{3}\left( {y - z} \right)\,\,or\,\,z \le y < 8 \Rightarrow G\left( y \right) = \frac{1}{{36}}{\left( {y - z} \right)^2}\)

If \(\frac{1}{3}\left( {y - 2} \right) \ge 2\,or\,y \ge 8\, \Rightarrow G\left( y \right) = 1\)

Therefore, cdf of y is

\(G\left( y \right) = \left\{ \begin{array}{l}0\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,y < 2\\\frac{1}{{36}}\,\,\,\,\,\,\,\,\,\,\,\,z \le y < 8\\1\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,\,if\,y \ge 8\end{array} \right.\)

02

Calculating the CDF 

Pdf of Y is

\(\begin{aligned}f\left( y \right) &= \frac{{dG\left( y \right)}}{{dy}}\\ &= \frac{1}{{36}}\left( {2y - 4} \right)\end{aligned}\)

\(\) \(f\left( y \right) = \left\{ \begin{aligned} = \frac{1}{{18}}\left( {y - 2} \right)\,\,if\,\,z \le y < 8\\\,\,0\,\,\,\,\,\,\,if\,y < 2\,\,or\,y \ge 8\,\,\end{aligned} \right.\)

Hence the required pdf is \(f\left( y \right) = \left\{ \begin{array}{l} = \frac{1}{{18}}\left( {y - 2} \right)\,\,if\,\,z \le y < 8\\\,\,0\,\,\,\,\,\,\,if\,y < 2\,\,or\,y \ge 8\,\,\end{array} \right.\)

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Most popular questions from this chapter

Show that there does not exist any numbercsuch that the following function would be a p.f.:

\(f\left( x \right) = \left\{ \begin{array}{l}\frac{c}{x}\;\;\;\;for\;x = 1,2,...\\0\;\;\;\;otherwise\end{array} \right.\)

Suppose that a random variableXhas the binomial distribution

with parametersn=8 andp=0.7. Find Pr(X≥5)by using the table given at the end of this book. Hint: Use the fact that Pr(X≥5)=Pr(Y≤3), whereYhas thebinomial distribution with parametersn=8 andp=0.3.

Consider the situation described in Example 3.7.14. Suppose that \(\) \({X_1} = 5\) and\({X_2} = 7\)are observed.

a. Compute the conditional p.d.f. of \({X_3}\) given \(\left( {{X_1},{X_2}} \right) = \left( {5,7} \right)\).

b. Find the conditional probability that \({X_3} > 3\)given \(\left( {{X_1},{X_2}} \right) = \left( {5,7} \right)\)and compare it to the value of \(P\left( {{X_3} > 3} \right)\)found in Example 3.7.9. Can you suggest a reason why the conditional probability should be higher than the marginal probability?

Suppose that the n variables\({{\bf{X}}_{\bf{1}}}{\bf{ \ldots }}{{\bf{X}}_{\bf{n}}}\) form a random sample from the uniform distribution on the interval [0, 1]and that the random variables \({{\bf{Y}}_{\bf{1}}}\;{\bf{and}}\;{{\bf{Y}}_{\bf{n}}}\) are defined as in Eq. (3.9.8). Determine the value of \({\bf{Pr}}\left( {{{\bf{Y}}_{\bf{1}}} \le {\bf{0}}{\bf{.1}}\;{\bf{and}}\;{\bf{Y}}_{\bf{n}}^{} \le {\bf{0}}{\bf{.8}}} \right)\)

Question:A painting process consists of two stages. In the first stage, the paint is applied, and in the second stage, a protective coat is added. Let X be the time spent on the first stage, and let Y be the time spent on the second stage. The first stage involves an inspection. If the paint fails the inspection, one must wait three minutes and apply the paint again. After a second application, there is no further inspection. The joint pdf.of X and Y is

\(f\left( {x,y} \right) = \left\{ \begin{array}{l}\frac{1}{3}if\,1 < x < 3\,and\,0 < y < 1\\\frac{1}{6}if\,1 < x < 3\,and\,0 < y < 1\,\\0\,\,otherwise.\\\,\end{array} \right.\,\,\)

a. Sketch the region where f (x, y) > 0. Note that it is not exactly a rectangle.

b. Find the marginal p.d.f.’s of X and Y.

c. Show that X and Y are independent.

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