Finding the pdf of a random variable which is a function of another rv

In summary, the conversation discusses the computation of E(X) and E(Y) for a given density function. It also delves into the determination of the density function for Y using the formula F_{Y}(y)=F_{X}(g^{-1}(y)). However, this formula is incorrect and should be corrected to F_{Y}(y)=1 - F_{X}(1/y) to obtain the correct probability density.
  • #1
Charlotte87
21
0

Homework Statement


Let f(x)=x/8 be the density of X on [0,4], zero elsewhere.

a) Show that f(x) is a valid density and compute E(X)
b) Define Y=1/X. Calculate E(Y)
c) Determine the density function for Y

The Attempt at a Solution


a) is just really basic. I've solved that one.

b) Without any "fuss" about it, i set g(x)=1/x, and use the following formula
[itex]\int^4_0(1/x*x/8)[/itex] = 1/2

c) Here the problem starts... So from my lecture notes i know that
[itex]F_{Y}(y)=F_{X}(g^{-1}(y))[/itex]

Y=1/X --> X=1/Y=g^-1(y)

Using this i can write the above as
[itex]F_{Y}(y)=F_{X}(g^{-1}(1/y))[/itex]

the pdf is then:

[itex]f_{Y}(y)=f_{X}(1/y)*(-1/y^{2})[/itex]

From here, I do not know how to proceed, any clues?
 
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  • #2
Charlotte87 said:
c) Here the problem starts... So from my lecture notes i know that
[itex]F_{Y}(y)=F_{X}(g^{-1}(y))[/itex]

Y=1/X --> X=1/Y=g^-1(y)

Using this i can write the above as
[itex]F_{Y}(y)=F_{X}(g^{-1}(1/y))[/itex]
Should be just be [itex]F_{Y}(y)=F_{X}(1/y)[/itex]
[itex]f_{Y}(y)=f_{X}(1/y)*(-1/y^{2})[/itex]

From here, I do not know how to proceed, any clues?
Well that's actually your answer right there, if you just sub in [itex]f_{X}(1/y) = 1/(8y)[/itex] to your final equation. Though that solution is not quite correct, as the "prepackaged" equations have let you down.

To see that this is incorrect just subst in as above and you'll find that the result this gives you is,
[tex]f_{Y}(y) = -1/(8y^3)[/tex]

Clearly this is wrong (because of the negative sign).
 
  • #3
To do this problem without using the prepacked equations, just start by writing the definition of [itex]F_{Y}(y)[/itex] as,

[tex]F_{Y}(y) = P(\frac{1}{x} < y)[/tex]

which for +ive x,y is equivalent to,

[tex]F_{Y}(y) = P(x > \frac{1}{y})[/tex]

Now solve the above using the appropriate integral and then differentiate wrt y to find [itex]f_{Y}(y)[/itex].
 
  • #4
uart said:
Should be just be [itex]F_{Y}(y)=F_{X}(1/y)[/itex]



Well that's actually your answer right there, if you just sub in [itex]f_{X}(1/y) = 1/(8y)[/itex] to your final equation. Though that solution is not quite correct, as the "prepackaged" equations have let you down.

To see that this is incorrect just subst in as above and you'll find that the result this gives you is,
[tex]f_{Y}(y) = -1/(8y^3)[/tex]

Clearly this is wrong (because of the negative sign).

The statement
[tex] F_Y(y) = F_X(1/y) [/tex] is incorrect. It should be
[tex] F_Y(y) = 1 - F_X(1/y), [/tex]
because [itex] \Pr\{ Y \leq y \} = \Pr \{ X \geq 1/y \}.[/itex] Now when you differentiate wrt y you get the correct probability density.

RGV
 
  • #5
Ray Vickson said:
The statement
[tex] F_Y(y) = F_X(1/y) [/tex] is incorrect. It should be
[tex] F_Y(y) = 1 - F_X(1/y), [/tex]
because [itex] \Pr\{ Y \leq y \} = \Pr \{ X \geq 1/y \}.[/itex] Now when you differentiate wrt y you get the correct probability density.

RGV

Hi Ray. I was merely pointing out that the statement [itex]F_Y(y) = F_X(1/y) [/itex] is what the OP should have written at that point if they had correctly substituted into the previous line of their own derivation. I clearly pointed out however, that it was not the correct way to do the problem. :)
 
Last edited:

Related to Finding the pdf of a random variable which is a function of another rv

1. What is the definition of a random variable?

A random variable is a variable whose possible values are outcomes of a random phenomenon. It is often denoted by a letter, such as X or Y, and can take on numerical values based on the outcome of a random experiment.

2. How is a random variable related to a function of another random variable?

A function of a random variable is a new random variable that is determined by applying a particular function to the values of the original random variable. This means that the values of the new random variable are dependent on the values of the original random variable.

3. What is the probability density function (PDF) of a random variable?

The probability density function (PDF) of a random variable is a function that describes the probability distribution of that particular random variable. It assigns a probability to each possible value of the random variable, and the total area under the curve is equal to 1.

4. How do you find the PDF of a function of another random variable?

To find the PDF of a function of another random variable, you can use the change of variables method. This involves substituting the original random variable into the function and then solving for the new random variable. The PDF of the new random variable can then be found using the chain rule and the PDF of the original random variable.

5. Why is finding the PDF of a function of another random variable important?

Finding the PDF of a function of another random variable is important because it allows us to analyze the probability distribution of the new random variable. This can be useful in various statistical and scientific applications, such as predicting the likelihood of certain outcomes or estimating the parameters of a system.

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