Joint problem density function problem

In summary, the conversation discusses forming a range for a question involving a density function in x and y. The question is clarified to have a range of 0≤y≤x≤∞ and the speaker asks if they will be able to find P(x+y≤1) after determining A through finding the "total" probability.
  • #1
Lewis7879
6
0
I need help guys I can't understand this
Can anyone explain thoroughly how do I form the range for this question?
f(x,y)= e-x for 0≤x≤y≤∞
0 Otherwise

Find P(x+y≤1)
I attempted this by integrating through the range of
0≤y≤(1-x) and 0≤x≤∞ but that doesn't seem right
 
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  • #2
The statement is confusing. You appear to have a density function in x and y, which is a function of x only.
 
  • #3
mathman said:
The statement is confusing. You appear to have a density function in x and y, which is a function of x only.
Hello mathman there's a slight error with range I made in the question which is 0≤y≤x≤∞
There was no other problems with the question as I was asked this way.
 
  • #4
No, [itex]f(x,y)= e^{-x}[/itex] for [itex]0\le x\le y\le A[/itex] is a function of both x and y. To determine "A", use the fact that the "total" probability must be 1:
[tex]\int_{y= 0}^A\int_{x= 0}^y e^{-x} dx dy= 1[/tex]
 
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  • #5
Getting an equation for A is easy enough. [itex]A+e^{-A}=2[/itex]. I am confused as to what is the question.
 
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  • #6
HallsofIvy said:
No, [itex]f(x,y)= e^{-x}[/itex] for [itex]0\le x\le y\le A[/itex] is a function of both x and y. To determine "A", use the fact that the "total" probability must be 1:
[tex]\int_{y= 0}^A\int_{x= 0}^y e^{-x} dx dy= 1[/tex]
Will I be able to find P(x+y≤1) after determine A?
 

Related to Joint problem density function problem

1. What is a joint problem density function?

A joint problem density function is a mathematical function that describes the probability of two or more variables occurring together. It is commonly used in statistics to analyze the relationship between variables and make predictions.

2. How is a joint problem density function different from a regular probability function?

A regular probability function only deals with one variable, while a joint problem density function deals with multiple variables simultaneously. It takes into account the probability of all possible combinations of the variables occurring together.

3. How is a joint problem density function used in data analysis?

A joint problem density function is used to model the relationship between variables and determine the probability of certain outcomes. It can also be used to identify patterns and trends in data and make predictions based on the relationship between variables.

4. What are the assumptions made when using a joint problem density function?

The main assumptions made when using a joint problem density function are that the variables are independent of each other and that the data follows a specific distribution, such as a normal or exponential distribution.

5. Can a joint problem density function be used for continuous and discrete variables?

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

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