Probability Density Function Notation












0












$begingroup$


So Im new to pdf's and am doing some preliminary research on the topic. I came across notation that I didn't understand. The problem I found said this:




A random variable I has the following PDF:



$P_i(i) = frac{4i}{a^2} U(i)$



where the variable i is simple the value of the random variable I.
Determine the PDF of the new random variable:



$X = frac{1}{I}$



using the following approaches:
a) the direct technique, i.e.,
calculating the Jacobian of the inverse transformation, etc., and b)
by first determining the CDF of the new RV, X, and then
differentiating.




In the notation above, what does the U(i) mean. Is it specifying a uniform distribution?










share|cite|improve this question











$endgroup$












  • $begingroup$
    Can you supply the reference to that problem?
    $endgroup$
    – JimB
    Dec 8 '18 at 5:16










  • $begingroup$
    @JimB I've updated the question to show the full question that was asked. It's just a random problem from a probability textbook
    $endgroup$
    – crazyCoder
    Dec 8 '18 at 5:25












  • $begingroup$
    Not all spaces have uniform distributions. In particular, any unbounded subset of $Bbb R$ does not. So unless $I$ is restricted to some bounded range, $U(i)$ cannot be a uniform distribution. You need to search the context of this problem in the textbook to figure out what $U(i)$ is supposed to be.
    $endgroup$
    – Paul Sinclair
    Dec 8 '18 at 14:40
















0












$begingroup$


So Im new to pdf's and am doing some preliminary research on the topic. I came across notation that I didn't understand. The problem I found said this:




A random variable I has the following PDF:



$P_i(i) = frac{4i}{a^2} U(i)$



where the variable i is simple the value of the random variable I.
Determine the PDF of the new random variable:



$X = frac{1}{I}$



using the following approaches:
a) the direct technique, i.e.,
calculating the Jacobian of the inverse transformation, etc., and b)
by first determining the CDF of the new RV, X, and then
differentiating.




In the notation above, what does the U(i) mean. Is it specifying a uniform distribution?










share|cite|improve this question











$endgroup$












  • $begingroup$
    Can you supply the reference to that problem?
    $endgroup$
    – JimB
    Dec 8 '18 at 5:16










  • $begingroup$
    @JimB I've updated the question to show the full question that was asked. It's just a random problem from a probability textbook
    $endgroup$
    – crazyCoder
    Dec 8 '18 at 5:25












  • $begingroup$
    Not all spaces have uniform distributions. In particular, any unbounded subset of $Bbb R$ does not. So unless $I$ is restricted to some bounded range, $U(i)$ cannot be a uniform distribution. You need to search the context of this problem in the textbook to figure out what $U(i)$ is supposed to be.
    $endgroup$
    – Paul Sinclair
    Dec 8 '18 at 14:40














0












0








0





$begingroup$


So Im new to pdf's and am doing some preliminary research on the topic. I came across notation that I didn't understand. The problem I found said this:




A random variable I has the following PDF:



$P_i(i) = frac{4i}{a^2} U(i)$



where the variable i is simple the value of the random variable I.
Determine the PDF of the new random variable:



$X = frac{1}{I}$



using the following approaches:
a) the direct technique, i.e.,
calculating the Jacobian of the inverse transformation, etc., and b)
by first determining the CDF of the new RV, X, and then
differentiating.




In the notation above, what does the U(i) mean. Is it specifying a uniform distribution?










share|cite|improve this question











$endgroup$




So Im new to pdf's and am doing some preliminary research on the topic. I came across notation that I didn't understand. The problem I found said this:




A random variable I has the following PDF:



$P_i(i) = frac{4i}{a^2} U(i)$



where the variable i is simple the value of the random variable I.
Determine the PDF of the new random variable:



$X = frac{1}{I}$



using the following approaches:
a) the direct technique, i.e.,
calculating the Jacobian of the inverse transformation, etc., and b)
by first determining the CDF of the new RV, X, and then
differentiating.




In the notation above, what does the U(i) mean. Is it specifying a uniform distribution?







probability density-function






share|cite|improve this question















share|cite|improve this question













share|cite|improve this question




share|cite|improve this question








edited Dec 8 '18 at 5:30







crazyCoder

















asked Dec 8 '18 at 5:05









crazyCodercrazyCoder

1012




1012












  • $begingroup$
    Can you supply the reference to that problem?
    $endgroup$
    – JimB
    Dec 8 '18 at 5:16










  • $begingroup$
    @JimB I've updated the question to show the full question that was asked. It's just a random problem from a probability textbook
    $endgroup$
    – crazyCoder
    Dec 8 '18 at 5:25












  • $begingroup$
    Not all spaces have uniform distributions. In particular, any unbounded subset of $Bbb R$ does not. So unless $I$ is restricted to some bounded range, $U(i)$ cannot be a uniform distribution. You need to search the context of this problem in the textbook to figure out what $U(i)$ is supposed to be.
    $endgroup$
    – Paul Sinclair
    Dec 8 '18 at 14:40


















  • $begingroup$
    Can you supply the reference to that problem?
    $endgroup$
    – JimB
    Dec 8 '18 at 5:16










  • $begingroup$
    @JimB I've updated the question to show the full question that was asked. It's just a random problem from a probability textbook
    $endgroup$
    – crazyCoder
    Dec 8 '18 at 5:25












  • $begingroup$
    Not all spaces have uniform distributions. In particular, any unbounded subset of $Bbb R$ does not. So unless $I$ is restricted to some bounded range, $U(i)$ cannot be a uniform distribution. You need to search the context of this problem in the textbook to figure out what $U(i)$ is supposed to be.
    $endgroup$
    – Paul Sinclair
    Dec 8 '18 at 14:40
















$begingroup$
Can you supply the reference to that problem?
$endgroup$
– JimB
Dec 8 '18 at 5:16




$begingroup$
Can you supply the reference to that problem?
$endgroup$
– JimB
Dec 8 '18 at 5:16












$begingroup$
@JimB I've updated the question to show the full question that was asked. It's just a random problem from a probability textbook
$endgroup$
– crazyCoder
Dec 8 '18 at 5:25






$begingroup$
@JimB I've updated the question to show the full question that was asked. It's just a random problem from a probability textbook
$endgroup$
– crazyCoder
Dec 8 '18 at 5:25














$begingroup$
Not all spaces have uniform distributions. In particular, any unbounded subset of $Bbb R$ does not. So unless $I$ is restricted to some bounded range, $U(i)$ cannot be a uniform distribution. You need to search the context of this problem in the textbook to figure out what $U(i)$ is supposed to be.
$endgroup$
– Paul Sinclair
Dec 8 '18 at 14:40




$begingroup$
Not all spaces have uniform distributions. In particular, any unbounded subset of $Bbb R$ does not. So unless $I$ is restricted to some bounded range, $U(i)$ cannot be a uniform distribution. You need to search the context of this problem in the textbook to figure out what $U(i)$ is supposed to be.
$endgroup$
– Paul Sinclair
Dec 8 '18 at 14:40










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