The joint density function of random variables X and Y is given as follows: Find: (a) P{Y > 2} (b) P{1 < X + Y < 3}

A First Course in Probability (10th Edition)
10th Edition
ISBN:9780134753119
Author:Sheldon Ross
Publisher:Sheldon Ross
Chapter1: Combinatorial Analysis
Section: Chapter Questions
Problem 1.1P: a. How many different 7-place license plates are possible if the first 2 places are for letters and...
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The joint density function of random variables X and Y is given as follows:

Find:

(a) P{Y > 2}

(b) P{1 < X + Y < 3}

The image represents the joint probability density function (PDF) of two continuous random variables, \(X\) and \(Y\). 

The function \( f_{XY}(x, y) \) is defined as follows:

\[
f_{XY}(x, y) = 
\begin{cases} 
e^{-(x+y)}, & \text{for } x, y > 0 \\ 
0, & \text{otherwise}
\end{cases}
\]

### Explanation:

- **Function \( e^{-(x+y)} \):** This part of the function applies when both \(x\) and \(y\) are greater than zero. It represents the joint probability density in this region.
  
- **Zero Otherwise:** The function is zero in the case where either \(x\) or \(y\) are not greater than zero, indicating that there is no probability mass outside the positive quadrant of the xy-plane.

### Context:

This type of function is useful in probabilistic studies and statistical methods for continuous data to understand the likelihood of different combinations of values for \(x\) and \(y\). The exponential decay suggests that higher values of \(x\) and \(y\) are less likely.
Transcribed Image Text:The image represents the joint probability density function (PDF) of two continuous random variables, \(X\) and \(Y\). The function \( f_{XY}(x, y) \) is defined as follows: \[ f_{XY}(x, y) = \begin{cases} e^{-(x+y)}, & \text{for } x, y > 0 \\ 0, & \text{otherwise} \end{cases} \] ### Explanation: - **Function \( e^{-(x+y)} \):** This part of the function applies when both \(x\) and \(y\) are greater than zero. It represents the joint probability density in this region. - **Zero Otherwise:** The function is zero in the case where either \(x\) or \(y\) are not greater than zero, indicating that there is no probability mass outside the positive quadrant of the xy-plane. ### Context: This type of function is useful in probabilistic studies and statistical methods for continuous data to understand the likelihood of different combinations of values for \(x\) and \(y\). The exponential decay suggests that higher values of \(x\) and \(y\) are less likely.
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