Probability density function of uniform distribution

AI Thread Summary
The discussion focuses on finding the probability density function (PDF) of the random variable Y, defined as Y = √X + 1, where X is uniformly distributed on the interval [0, 1]. Participants clarify the transformation from Y to X and the correct formulation of the cumulative distribution function (CDF) F_Y(y) based on the relationship between Y and X. Key points include ensuring that the range of Y is correctly identified as [1, 2] and that the CDF should reflect this range. The final PDF f_Y(y) is derived by differentiating the CDF and must include appropriate constraints. Overall, the conversation emphasizes correcting errors in the transformation process to arrive at the correct PDF for Y.
diracdelta
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Homework Statement


Random variable X is uniformly distributed on interval [0,1]:
f(x)=\begin{cases} 1 & \text{ if } 0\leq x\leq 1\\ 0 & \text{ else} \end{cases}

a) Find probability density function ρ(y) of random variable Y=\sqrt{X} +1

I tried like this. Is it good, if no why not?

F_{Y}(y)=P(Y\leq y)=P(x^{2}+1\leq y)=P(x\leq y^{2}+1)=F_{x}(y^{2}+1) \\ f_{X}(x)=F_{X}'(y^{2}+1)=f_{X}(y^{2}+1)* \left | \frac{d}{dy} (y^{2}+1)\right |=f_{X}(y^{2}+1)*2y \\ f_{Y}(y)=\begin{cases} 2y & \text{ if } 1\leq x\leq 2\\ 0 & \text{ else} \end{cases}
 
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diracdelta said:

Homework Statement


Random variable X is uniformly distributed on interval [0,1]:
f(x)=\begin{cases} 1 & \text{ if } 0\leq x\leq 1\\ 0 & \text{ else} \end{cases}

a) Find probability density function ρ(y) of random variable Y=\sqrt{X} +1

I tried like this. Is it good, if no why not?

F_{Y}(y)=P(Y\leq y)=P(x^{2}+1\leq y)=P(x\leq y^{2}+1)=F_{x}(y^{2}+1) \\ f_{X}(x)=F_{X}'(y^{2}+1)=f_{X}(y^{2}+1)* \left | \frac{d}{dy} (y^{2}+1)\right |=f_{X}(y^{2}+1)*2y \\ f_{Y}(y)=\begin{cases} 2y & \text{ if } 1\leq x\leq 2\\ 0 & \text{ else} \end{cases}
How did \sqrt{X}+ 1 become X^2+ 1? If you intended the inverse function then it should be X= (Y- 1)^2
 
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Hmm, i see.
Ok then, i get this
F_{Y}(y)=P(Y\leq y)=P(x^{1/2}+1\leq y)=P(x\leq (y+1)^{2}) =F_{x}(y+1)^{2} \\ f_{X}(x)=F_{X}'(y+1)^{2}=f_{X}(y+1)^{2}* \left | \frac{d}{dy} (y+1)^{2})\right |=f_{X}(y+1)^{2})*2y \\ f_{Y}(y)=\begin{cases} 2y & \text{ if } 1\leq x\leq 2\\ 0 & \text{ else} \end{cases}[/QUOTE]

But what about y's probability density function ?
Is it ok?
 
diracdelta said:
##F_{Y}(y)=P(Y\leq y)=P(x^{\frac 12}+1\leq y)##
That should really be
##F_{Y}(y)=P(Y\leq y)=P(X^{\frac 12}+1\leq y)##
diracdelta said:
##=P(x\leq (y+1)^{2}) ##
Check that step.
diracdelta said:
##f_{X}(x)=F_{X}'(y+1)^{2}=f_{X}(y+1)^{2}* \left | \frac{d}{dy} (y+1)^{2})\right |##
##F_{X}'((y+1)^{2})## just means the derivative wrt x of FX(x) evaluated at x = (y+1)2
##f_{X}(x)=F_{X}'((y+1)^{2})=f_{X}((y+1)^{2})##
 
diracdelta said:
Hmm, i see.
Ok then, i get this
F_{Y}(y)=P(Y\leq y)=P(x^{1/2}+1\leq y)=P(x\leq (y+1)^{2}) =F_{x}(y+1)^{2} \\ f_{X}(x)=F_{X}'(y+1)^{2}=f_{X}(y+1)^{2}* \left | \frac{d}{dy} (y+1)^{2})\right |=f_{X}(y+1)^{2})*2y \\ f_{Y}(y)=\begin{cases} 2y & \text{ if } 1\leq x\leq 2\\ 0 & \text{ else} \end{cases}

But what about y's probability density function ?
Is it ok?[/QUOTE]

How do you get from ##x^{1/2}+1 \leq y## to ##x \leq (y+1)^2##? (I don't.)

Anyway, since ##X## ranges from 0 to 1, so does ##\sqrt{X}## and that means that ##Y = 1 + \sqrt{X}## ranges from 1 to 2. So, you ought to have ##F_Y(1) = 0## and ##F_Y(2) = 1##. Do you have that?
 
Last edited:
diracdelta said:
F_{Y}(y)=P(Y\leq y)=P(x^{1/2}+1\leq y)=P(x\leq (y+1)^{2}) =F_{x}(y+1)^{2}
Up to here it's OK, except for the two errors pointed out by haruspex. Fix those and you will have a correct formula for ##F_Y(y)## in terms of ##F_X## applied to some function of ##y##.

Next you can use the fact that ##F_X(x)=\int_0^x f_X(u)du=\int_0^x du=x## to write a formula for ##F_{Y}(y)## in terms of ##y##.

Forget about everything you wrote below your first line, as that heads off on a goose chase involving ##f_X## and there is no need to refer to ##f_X## any further.

Differentiating your formula for ##F_Y(y)## will give you a formula for ##f_Y(y)##.

To complete the answer you need to put range constraints into your expression for ##f_Y##, along the lines suggested by Ray.
 

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