How to Calculate the Expected Value of X Given Y=5?

It is not hard to solve the problem, but it does require care in your calculations.In summary, the problem involves calculating the expected value of X given Y=5 in a joint probability distribution with two components, X and Y, each with a lifetime between 0 and 10. The solution involves setting up an integral with the appropriate limits and solving for the expected value. It is important to carefully check each step to avoid errors.
  • #1
mynameisfunk
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Homework Statement


A machine consists of 2 components whose lifetimes are X and Y and have joint pdf,
[tex] f(x,y)=1/50[/tex] w/ [tex]0<x<10[/tex], [tex]0<y<10[/tex],[tex]0<x+y<10 [/tex]
Calculate the expected value of [tex]X [/tex] given [tex]Y=5[/tex].

Homework Equations


[tex]E[X|Y]= \int_{-inf}^{inf} x f(x,y)/f(y) dx[/tex]


The Attempt at a Solution


[tex]f(y) = \int_{0}^{10-y} 1/50 dx = (1-y)/5[/tex]

[tex]E[x|y] = \int_{0}^{10-y} x/(10-10y) dx [/tex]

This is where I am confused. How do i set the limits on the integral where I actually compute the expectation? Is x=0 to x=10-y right? I was thinking I want to just integrate as normal and plug in y=5 after the integration.
 
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  • #2
mynameisfunk said:

Homework Statement


A machine consists of 2 components whose lifetimes are X and Y and have joint pdf,
[tex] f(x,y)=1/50[/tex] w/ [tex]0<x<10[/tex], [tex]0<y<10[/tex],[tex]0<x+y<10 [/tex]
Calculate the expected value of [tex]X [/tex] given [tex]Y=5[/tex].

Homework Equations


[tex]E[X|Y]= \int_{-inf}^{inf} x f(x,y)/f(y) dx[/tex]


The Attempt at a Solution


[tex]f(y) = \int_{0}^{10-y} 1/50 dx = (1-y)/5[/tex]

[tex]E[x|y] = \int_{0}^{10-y} x/(10-10y) dx [/tex]

This is where I am confused. How do i set the limits on the integral where I actually compute the expectation? Is x=0 to x=10-y right? I was thinking I want to just integrate as normal and plug in y=5 after the integration.

Careful:
[tex]f(y) = \int_{0}^{10-y} 1/50 dx = \frac{10-y}{50} \neq (1-y)/5 \leftarrow \text{ what you wrote} [/tex]

So, you should have a different ##f(x|y)## from what you wrote, which means that ##E(X|Y=y)## will be different from what you wrote. And, finally, YES, you should put y = 5 after the integration (or even before the integration, since y is kept constant throughout).
 
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  • #3
thank you!

OK, thanks for that. OK, just to be clear, can you tell me if this looks right?

[ itex ]E[X|Y=5] = \int_{0}^{10} x E[X|Y=5] dx \int_{0}^{1} x * 1/5 dx = \left[ \frac{10}{2}x^2 \right]_{0}^{10} = 10[ /itex ]

Not sure why I can't get this latex to work but I am getting 10 for my answer. Does that seem right?
 
  • #4
mynameisfunk said:
OK, thanks for that. OK, just to be clear, can you tell me if this looks right?

[ itex ]E[X|Y=5] = \int_{0}^{10} x E[X|Y=5] dx \int_{0}^{1} x * 1/5 dx = \left[ \frac{10}{2}x^2 \right]_{0}^{10} = 10[ /itex ]

Not sure why I can't get this latex to work but I am getting 10 for my answer. Does that seem right?

Edited version of the above:
[tex]E[X|Y=5] = \int_{0}^{10} x E[X|Y=5] dx \int_{0}^{1} x * 1/5 dx = \left[ \frac{10}{2}x^2 \right]_{0}^{10} = 10[/tex]
(obtained by replacing "[ itex ]" by "[tex ]" (remove the space between 'x' and ']' and replacing "[ /itex ]" by "[/tex ]"', again removing the final space. If you want in-line formulas (such as produced by "[itex ]"---no spaces) it is easier to use "# #" (no space between the two #s) at each end of the formula.

Anyway, your formula is incomprehensible to me, and I cannot figure out why you would ever assume it is correct. It is essentially saying (for ##A = E[X|Y=5]##) that
[tex] A = \int_0^{10} A x \, dx \cdot \int_0^1 \frac{x}{5} dx.[/tex]
and that says
[tex] A = A \frac{100}{2} \cdot \frac{1}{2} \frac{1}{5} = 50 A,[/tex]
which could only be true for A = 0.

Go back to square one, and go carefully. Just take your time, and check every step.
 

FAQ: How to Calculate the Expected Value of X Given Y=5?

1. What is the concept of expected value in relation to joint probability distribution?

The expected value of a joint probability distribution is a measure of the central tendency of the distribution. It represents the average value that would be obtained if the experiment or process were repeated many times. It is calculated by multiplying each possible outcome by its probability and summing all of these products.

2. How is expected value used in decision making?

In decision making, expected value is used to determine the best course of action by considering all possible outcomes and their associated probabilities. It helps to assess the risk and potential rewards of different options and make a rational decision based on these factors.

3. Can expected value be negative?

Yes, expected value can be negative. This means that the potential outcomes of a situation have a higher probability of resulting in a loss rather than a gain. It is important to consider both the magnitude and probability of potential outcomes when evaluating expected value.

4. How does expected value relate to variance?

Expected value and variance are both measures of central tendency and variability within a probability distribution. Expected value represents the average outcome, while variance measures how much the actual outcomes vary from this average. A higher variance indicates a greater range of possible outcomes, which can impact the expected value.

5. What are some real-life applications of expected value in science?

Expected value is used in science to evaluate the potential outcomes of experiments or processes. For example, in clinical trials for new medications, expected value is used to assess the effectiveness and potential side effects based on different dosages. In economics, expected value is used to evaluate the potential returns and risks of different investment strategies. It is also commonly used in risk management and decision-making in fields such as insurance and finance.

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