Joint Probability Density Functions

In summary, the problem involves two birds landing on a power line with a distance of 100 feet between two utility poles. The first part of the problem involves finding the average distance between the two birds, which can be done by defining the random variables X and Y for the positions of the two birds and then finding the expected value of the distance between them. The second part of the problem involves a third bird landing on the line, but the distribution density function of Z provided is incorrect. It should be evaluated using the equation provided.
  • #1
lexluger
1
0
Problem:

Two birds have landed on a power line that spans the 100' distance between utility poles.
a) What is the average distance between the birds?
b) The line runs north and south. Another bird lands on the line. What is the expected position of the north-most bird from the south-most pole?

Partial Solution:

For the first part of the problem, I defined the first bird's position as the random variable $X$ and the second birds position as the random variable $Y$. Since both birds could lie in the range [0, 100], the plot of the birds' possible positions yielded a square with area $100^{2}$ feet$^{2}$. I then defined a new random variable, $Z$, to represent the distance between the two birds, defined by $|X-Y|$.Thus, the PDF of $Z$ can be written as $f_{Z}(z) = \begin{cases}
1/10000, & z\leq100 \\
0, & \text{otherwise }
\end{cases}
$.
From here, to find the average distance between the birds, I solved for the expected value of $Z$, using the equation $\int_{-\infty}^{\infty}\int_{-\infty}^{\infty}zf_{Z}(z)dydx$, which yielded that $E[Z] = E[|X-Y|] = 100/3$ feet.

So first and foremost, did I do this correctly?

Secondly, I am completely stuck on the second part of the problem.
 
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  • #2
lexluger said:
Problem:

Two birds have landed on a power line that spans the 100' distance between utility poles.
a) What is the average distance between the birds?
b) The line runs north and south. Another bird lands on the line. What is the expected position of the north-most bird from the south-most pole?

Partial Solution:

For the first part of the problem, I defined the first bird's position as the random variable $X$ and the second birds position as the random variable $Y$. Since both birds could lie in the range [0, 100], the plot of the birds' possible positions yielded a square with area $100^{2}$ feet$^{2}$. I then defined a new random variable, $Z$, to represent the distance between the two birds, defined by $|X-Y|$.Thus, the PDF of $Z$ can be written as $f_{Z}(z) = \begin{cases}
1/10000, & z\leq100 \\
0, & \text{otherwise }
\end{cases}
$.
From here, to find the average distance between the birds, I solved for the expected value of $Z$, using the equation $\int_{-\infty}^{\infty}\int_{-\infty}^{\infty}zf_{Z}(z)dydx$, which yielded that $E[Z] = E[|X-Y|] = 100/3$ feet.

So first and foremost, did I do this correctly?

Secondly, I am completely stuck on the second part of the problem.

Hi lexluger! Welcome to MHB! :)

I'm afraid your distribution density function of $Z$ is not correct.
Consider that:
$$f_Z(z) = \underbrace{\int_z^{100} f_X(x) f_Y(x - z)\,dx}_{x-y\ge 0} + \underbrace{\int_0^{z} f_X(x) f_Y(x + z)\,dx}_{x-y < 0}$$

Can you evaluate that?
 

FAQ: Joint Probability Density Functions

What is a joint probability density function (PDF)?

A joint probability density function is a mathematical function that describes the probability of multiple random variables occurring simultaneously. It is used to model the probability distribution of a set of variables and is typically denoted as f(x,y) for two variables or f(x1, x2, ..., xn) for n variables.

How is a joint PDF different from a regular PDF?

A regular probability density function describes the likelihood of a single random variable occurring at a specific value. In contrast, a joint PDF takes into account multiple variables and their potential combinations, providing a more comprehensive representation of the probability distribution.

How is a joint PDF used in statistical analysis?

Joint PDFs are commonly used in statistical analysis to evaluate the probability of multiple events occurring together. They can also be used to calculate other important measures such as covariance and correlation between variables.

What is the relationship between a joint PDF and a joint cumulative distribution function (CDF)?

A joint CDF is the cumulative sum of the joint PDF and represents the probability that the variables are less than or equal to a given value. The joint CDF can be obtained by integrating the joint PDF over the desired range of values.

Can a joint PDF be used for continuous and discrete variables?

Yes, a joint PDF can be used for both continuous and discrete variables. For continuous variables, it is represented as a continuous function, while for discrete variables, it is represented as a discrete function.

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