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Math Help Please

D

DVK916

Banned
Given two random variables X and Y, let Y have a non probabilistic measure with infinite cumulative density, and let X|Y have a probability measure with cumulative density of 1. Prove that X must also have a non probabilistic measure with infinite cumulative density.

Essentially prove this.

Given Integral(fy(y)dy)=infiniti
Integral(fx|y(x|y)dx)=1

Then

Integral(fx(x)dx)= infiniti.
 
Um.... can you write it out with better symbols? How bout write it in Scientific Notebook or something and upload the screen shot to pics.bbzzdd?
 
huh? Whatdhe say?

/me is pretty math challenged...I do ok with basic elementary algebra...sometimes, but after that, it might as well be Chinese...School is gonna be fun the next couple of semesters...Math in each one...
 
I find your definition of "low level math" disturbing.
:Q

I've had Calc I and II, and this is like nothing I've ever seen before.
 
Originally posted by: Jeff7
I find your definition of "low level math" disturbing.
:Q

I've had Calc I and II, and this is like nothing I've ever seen before.
Click to expand...

OP is just trying to show off. Don't be alarmed. Probability and random variables aren't trivial as demonstrated by the OP.
 
yeah, this is one of those probability concepts I remember using it in my quantum class. We called it dirac integral or sth...
 
This is what I have

Integral(fx(x)dx)=integral(integral(f(x|y)*f(y)dy)dx)

Now this integral isn't seperatable since f(x|y) is a function of both x and y.

So I can't just say it equals 1*infiniti which is wrong.

 
This was on my Final on my Advanced Bayesian Probability course. It is a high level course with Calculus probability theory as a prequirement.
 
I also want the proof for the discrete case. I have trying to do this problem since our final when I couldn't do it. Got a B in the class though. Still sucks.
 
Originally posted by: DVK916
This was on my Final on my Advanced Bayesian Probability course. It is a high level course with Calculus probability theory as a prequirement.
Click to expand...

SO WHY DID YOU CALL IT BASIC? If I can't figure it out, and I know Diff EQ. and 3 semesters of Calc, IT'S NOT BASIC!!
 
Originally posted by: Tick
Originally posted by: DVK916
This was on my Final on my Advanced Bayesian Probability course. It is a high level course with Calculus probability theory as a prequirement.
Click to expand...

SO WHY DID YOU CALL IT BASIC? If I can't figure it out, and I know Diff EQ. and 3 semesters of Calc, IT'S NOT BASIC!!
Click to expand...

Well I thought by calling it basic would get more people to look at it, calling it advance might scare people away.
 
Integral(f_Y(y) dy) = infinity from c to d
Integral(f_X(x|Y=y) dx) = 1 from a to b

You know that f_X(x|Y=y) = f_XY(x,y)/f_Y(y))

Substitute above

Integral(f_X(x|Y=y) dx) = 1 --> Integral(f_XY(x,y)/f_Y(y)) dx) = 1 [with limits a to b]
Since f_Y(y) is independent of x, you can take it out of the integral and put it on the other side.

Integral(f_XY(x,y) dx) = f_Y(y) [with limits a to b]

Now, take the integral with respect to y of both sides [with limits c to d]

See picture here
 
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