The Joint PDF of Two Uniform Distributions

In summary: This means that the probability of finding any x value between 10 and 10.57 and any y value between 10 and 10.57 is the same. The fraction in the denominator is just the numerator divided by the sum of the numerators.
  • #1
tamuag
9
0

Homework Statement


A manufacturer has designed a process to produce pipes that are 10 feet long. The distribution of the pipe length, however, is actually Uniform on the interval 10 feet to 10.57 feet. Assume that the lengths of individual pipes produced by the process are independent. Let X and Y represent the lengths of two different pipes produced by the process.

What is the joint pdf for X and Y?

Homework Equations

The Attempt at a Solution


My roommate says the answer is [itex]f(x,y) = 1 / 0.57^2, 10 \leq x \leq 10.57, 10 \leq y \leq10.57[/itex]

I understand why [itex]10 \leq x \leq 10.57, 10 \leq y \leq 10.57[/itex], but why is [itex]f(x,y) = 1 / 0.57^2[/itex]?

My thoughts so far:
Isn't [itex]f(x,y) = 1 / 0.57^2[/itex] really just [itex]f(x,y) = (1 / 0.57)(1 / 0.57)[/itex], where [itex]f(x) = f(y) = 1 / 0.57[/itex]?

What I really don't understand is why [itex]f(x) = 1 / 0.57[/itex] in the first place? Where does that term come from? I get that it's a constant because the distribution is uniform, but why is it a fraction and why is the denominator [itex]0.57[/itex]?
 
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  • #2
##f(x) = \frac{1}{0.57}## because ## \int_{10}^{10.57} f(x) dx = 1## and ##f(x)## is constant.
 
  • #3
tamuag said:

Homework Statement


A manufacturer has designed a process to produce pipes that are 10 feet long. The distribution of the pipe length, however, is actually Uniform on the interval 10 feet to 10.57 feet. Assume that the lengths of individual pipes produced by the process are independent. Let X and Y represent the lengths of two different pipes produced by the process.

What is the joint pdf for X and Y?

Homework Equations

The Attempt at a Solution


My roommate says the answer is [itex]f(x,y) = 1 / 0.57^2, 10 \leq x \leq 10.57, 10 \leq y \leq10.57[/itex]

I understand why [itex]10 \leq x \leq 10.57, 10 \leq y \leq 10.57[/itex], but why is [itex]f(x,y) = 1 / 0.57^2[/itex]?

My thoughts so far:
Isn't [itex]f(x,y) = 1 / 0.57^2[/itex] really just [itex]f(x,y) = (1 / 0.57)(1 / 0.57)[/itex], where [itex]f(x) = f(y) = 1 / 0.57[/itex]?

What I really don't understand is why [itex]f(x) = 1 / 0.57[/itex] in the first place? Where does that term come from? I get that it's a constant because the distribution is uniform, but why is it a fraction and why is the denominator [itex]0.57[/itex]?

The random variables are uniform over intervals of length 0.57.
 

Related to The Joint PDF of Two Uniform Distributions

1. What is a joint PDF?

A joint PDF, or joint probability density function, is a mathematical function that describes the probability of two or more random variables occurring simultaneously. In other words, it maps out the likelihood of different outcomes for multiple variables at the same time.

2. What is the formula for the joint PDF of two uniform distributions?

The formula for the joint PDF of two uniform distributions is f(x,y) = 1/((b-a)(d-c)) for a ≤ x ≤ b and c ≤ y ≤ d. This means that the probability of a specific pair of values (x,y) occurring is equal to 1 divided by the total area of the rectangle formed by the range of values for both variables.

3. How is the joint PDF of two uniform distributions graphically represented?

The joint PDF of two uniform distributions is typically represented as a 3D surface plot, with the x and y axes representing the two variables and the z-axis representing the probability density. Alternatively, it can also be represented as a contour plot, with lines connecting points of equal probability density.

4. What does the shape of the joint PDF of two uniform distributions look like?

The shape of the joint PDF of two uniform distributions is a flat rectangle, with a constant probability density across the entire range of values for both variables. This is because a uniform distribution assumes that all values within a given range have an equal probability of occurring.

5. How is the joint PDF of two uniform distributions used in scientific research?

The joint PDF of two uniform distributions is used to model and analyze the relationships between two variables in scientific research. It can provide insights into the likelihood of certain outcomes and help identify patterns or correlations between the variables. It is commonly used in fields such as statistics, economics, and engineering.

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