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Conference rusure::math

Title:Mathematics at DEC
Moderator:RUSURE::EDP
Created:Mon Feb 03 1986
Last Modified:Fri Jun 06 1997
Last Successful Update:Fri Jun 06 1997
Number of topics:2083
Total number of notes:14613

1135.0. "Random variables problem" by WFOV11::PLANTE () Sat Oct 07 1989 19:19

This problem came up as a homework problem from a Random Signals and Noise 
course I am presently taking.  The problem has two parts: (1) find the 
probability density function (pdf) of Z given that Z=X+2Y and (2) Find 
P[0<Z<=1].  The answer from (1) should give the answer to (2) by integrating 
from z=0 to z=1.

Here is the problem statement:

Use convolution to find the probabilty density function of Z given that Z=X+2Y
where f (x) and f (y) are defined as:
       X         Y

                         [   2x     0<x<=1
                 f (x) = [
                  X      [   0      elsewhere

"Y is uniformly distributed over the range -1 to 1"  which I translated to:

                            [ 1/2   -1 < y <= 1
                    f (y) = [
                            [ 0      elsewhere

                                  oo                     ("oo" is "infinity")
Using convolution, f (z)= integral [ f (x) f ((z-x)/2) dx ]
                    Z            -oo  X     Y


My answer for f (z) was:
               Z
                              [  0                       z <= 0
                              [  (1/2)z**2               0 < z <= 1
                     f (z) =  [  (1/2)                   1 < z <= 2
                      Z       [  (1/2)-(1/2)(z-2)**2     2 < z <= 3
                              [  0                       z > 3

This looked good because the integral over -oo to +oo is 1, a property
of pdf's  (see note below for other attempts).

Using the above to do part (2), I get an answer of 1/6 when I integrate f(z)
from 0 to 1.  However, the book gives an answer of 1/4 ... which can be 
obtained by integrating the triangular region under y=(1-x)/2 from x=0 to 
x=1 (this is the region for which 0<x+2y<=1).

Can someone tell me where I went wrong?
    
Thanks in advance!
Al
  
PS: Here are the other f ((z-x)/2)'s I have tried: 
                        Y

I had a hard time picking what f ((z-x)/2) should look like so I tried the 
                                Y
"picture" approach to get a rectangle with height 1/2 and base 2.  When I 
took the "mathematical" approach the base of the rectangle became 4 which 
left me wondering if I should adjust the height to be 1/4 instead of 1/2 
(area should be 1?).

With f ((z-x)/2) taken to be a rectangle with base of 4 and height of 1/4:
      Y
                          [  0                     z <= 0
                          [  (1/4)z**2             0 < z <= 1
                 f (z) =  [  1/4                   1 < z <= 4
                  Z       [  (1/4)-(1/4)(z-4)**2   4 < z <= 5
                          [  0                     z > 5
                     (this also integrates to 1 over -oo to +oo)

With f ((z-x)/2) taken to be a rectangle with base of 4 and height of 1/2:
      Y
                          [  0                      z <= 0
                          [  (1/2)z**2              0 < z <= 1
                  f (z) = [  1/2                    1 < z <= 4
                   Z      [  (1/2)-(1/2)(z-4)**2    4 < z <= 5
                          [  0                      z > 5

Neither of the above f(z)'s gives an answer of 1/4 for P[0<Z<=1].

T.RTitleUserPersonal
Name
DateLines
1135.1AITG::DERAMODaniel V. {AITG,ZFC}:: D'EramoSun Oct 08 1989 00:3922
        With probability 1/4, Y will be less than -1/2, and so 2Y
        will be less than -1 and Z=X+2Y will be less than 0.  Yet
        your solution for Z has Z always at least zero. 
        Therefore your solution for f (z) is incorrect.
                                     Z
        
        A correct solution for Z will have nonzero probability
        for -2 < Z < 3 and zero probability outside that range,
        with an overall probability of at least 1/4 that Z is
        negative (the case of the first paragraph occurs with
        probability 1/4 but does not exhaust all possibilities of
        negative Z).
        
        The probability that 0 < Z <= 1 will be the integral as y
        goes from -1/2 to 0 of (1/2)dy times Prob(x > 2|y|),
        plus the integral as y goes from 0 to 1/2 of (1/2)dy
        times Prob(x <= 1-2y).  Plugging in Prob(x > 2|y|) = 1 -
        4y^2 for y in -1/2 to 0, and Prob(x <= 1-2y) = (1-2y)^2
        for y in 0 to 1/2, gives Prob(0<Z<=1) = 1/6 + 1/12 = 1/4.
        
        Dan
        
1135.2My mistakeWFOVX5::PLANTESun Oct 08 1989 14:5231
                           
    RE -.1,
    Thank you Dan.
                                            
    When I flipped the rectangle, f (y) --> f ((z-x)/2), I came up with
                                   Y         Y
    the right edge being located at z+2, the left edge at z-2, and z 
    in the middle.  But, in evaluating the convolution integral, I used
    "z" to represent the leading (right) edge and "z-4" to represent the
    left edge -- that's where I was wrong.

    I had to use the rectangle with base=4, height=1/4.  The
    change in height was justified by noting that since the function
    should be a pdf, then the height is related to the base such that
    the overall area = 1.   
    
    My final answer was:
                                                          
                              [  0                        z <= -2
                              [  (1/4)(z+2)^2        -2 < z <= -1
                     f (z) =  [  1/4                 -1 < z <= 2
                      Z       [  (1/4)-(1/4)(z-2)^2   2 < z <= 3
                              [  0                        z > 3
    
                                                               
    This integrates to 1 over (-oo, +oo) and also gives P[0<Z<=1]=1/4.
    Also, P[Z<=0]=1/3 > 1/4, and the pdf is nonzero only on (-2, 3] as 
    you mentioned.
    
    Thanks again.
    Al
1135.3AITG::DERAMODaniel V. {AITG,ZFC}:: D'EramoSun Oct 08 1989 18:246
        That satisfies two other tests:  it's weighted a little
        heavier at the top (like the X distribution is), and it
        combined linear and constant pdf's and came out
        quadratic.  So that's "probably" :-) it.
         
        Dan