Joint PDFs and Expected Values of 3 Cont Rand Vars

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In summary: Therefore,E(X_1^2X_2^3) = \frac {2}{7} \int_0^1 \frac {4}{7} 2x_1^3 \,dx_1 dx_2In summary, the problem asks for the expected value of 5X1X2X3.
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SpiffWilkie
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You know how sometimes, you take a long time to write a question, and then you submit, but it takes you to a login screen and then you lose everything you wrote?

Anyhow...I would just like to verify some work here.

The problems states that there are 3 mutually independent random variables, X1, X2, X3, each with the pdf f(x) = 2x, 0 < x < 1.

a) What is the joint pdf?
For this, I'm assuming I just need to take the product of the three pdfs, giving me 8x1x2x3?

b) Find the expected value of 5X1X2X3.
Am I to assume that this is equal to 5 * E(X1) * E(X2) * E(X3)? If that is true, I would calculate 5 * (∫2x2dx)3 from 0 to 1?
This gives the result 40/27 ≈ 1.48

c) Find P(X1 < 1/2, X2 < 1/2, X3 < 1/2)
I calculated (∫2xdx)3 from 0 to 1/2, giving me 1/64 or .015625I'm struggling trying to connect examples from class/book/internet with actual problems given, so any help is much appreciated.

Thanks,
Steve
 
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  • #2
SpiffWilkie said:
You know how sometimes, you take a long time to write a question, and then you submit, but it takes you to a login screen and then you lose everything you wrote?

Anyhow...I would just like to verify some work here.

The problems states that there are 3 mutually independent random variables, X1, X2, X3, each with the pdf f(x) = 2x, 0 < x < 1.

a) What is the joint pdf?
For this, I'm assuming I just need to take the product of the three pdfs, giving me 8x1x2x3?

b) Find the expected value of 5X1X2X3.
Am I to assume that this is equal to 5 * E(X1) * E(X2) * E(X3)? If that is true, I would calculate 5 * (∫2x2dx)3 from 0 to 1?
This gives the result 40/27 ≈ 1.48

c) Find P(X1 < 1/2, X2 < 1/2, X3 < 1/2)
I calculated (∫2xdx)3 from 0 to 1/2, giving me 1/64 or .015625


I'm struggling trying to connect examples from class/book/internet with actual problems given, so any help is much appreciated.

Thanks,
Steve

For (b): do not *assume*. This is something you should know. The short answer is 'yes' in this case---that is, that E(X1 X2 X3) = EX1 * EX2 * EX3----- but not in general. Do you know why?

If you are unsure, the best way is to write out everything in detail. For example, you can certainly say that
[tex] E(X_1 X_2 X_3) = \int_0^1 \int_0^1 \int_0^1 x_1 x_2 x_3 f(x_1,x_2,x_3) \, dx_1 \, dx_2 \, dx_3,[/tex]
and you can go on from there.

RGV
 
  • #3
Ray Vickson said:
For (b): do not *assume*. This is something you should know. The short answer is 'yes' in this case---that is, that E(X1 X2 X3) = EX1 * EX2 * EX3----- but not in general. Do you know why?

If you are unsure, the best way is to write out everything in detail. For example, you can certainly say that
[tex] E(X_1 X_2 X_3) = \int_0^1 \int_0^1 \int_0^1 x_1 x_2 x_3 f(x_1,x_2,x_3) \, dx_1 \, dx_2 \, dx_3,[/tex]
and you can go on from there.

RGV
So, in your equation, then just integrate [tex] \int_0^1 2x_3^2 dx_3 [/tex] substituting that into the integral for x2, and then that result into the integral for x1?
Actually, the explanation helped me out with another problem:

[tex] f(x_1) = 2x_1, 0 < x_1 < 1 and f(x_2) = 4x_2^3, 0 < x_2 < 1[/tex]

so, [tex]E(X_1^2X_2^3) = \int_0^1 \int_0^1 x_1^2 x_2^3 f(x_1,x_2) \, dx_1 \, dx_2 [/tex]
[tex] = \int_0^1 \frac {4}{7} 2x_1^3 \,dx_1 [/tex]
[tex] = \frac {2}{7} [/tex]
 

Related to Joint PDFs and Expected Values of 3 Cont Rand Vars

1. What is a joint probability density function (PDF)?

A joint probability density function is a mathematical function that describes the probability of multiple continuous random variables taking on specific values simultaneously. It can be used to calculate the probability of events involving multiple variables.

2. How is a joint PDF different from a regular PDF?

A regular PDF describes the probability of a single random variable taking on specific values. A joint PDF takes into account multiple random variables and calculates the probability of all of them occurring together.

3. What is the expected value of a joint PDF?

The expected value of a joint PDF is the weighted average of all possible values that the variables can take on, with the weights being the probabilities of those values occurring. It is similar to the expected value of a regular PDF, but takes into account multiple variables.

4. How do you calculate the expected value of 3 continuous random variables?

To calculate the expected value of 3 continuous random variables, you need to first find the joint PDF of the variables. Then, you can use the formula E(X,Y,Z) = ∫∫∫ x*y*z*f(x,y,z) dx dy dz, where x,y,z are the variables and f(x,y,z) is the joint PDF. This involves solving a triple integral.

5. What is the significance of the expected value in relation to joint PDFs and continuous random variables?

The expected value is a measure of central tendency for a set of data. In the context of joint PDFs and continuous random variables, it represents the average value of all possible outcomes. It is useful for making predictions and making decisions based on probabilities.

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