Finding PDF of uniform distribution

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The discussion revolves around demonstrating that the random variable Y, defined as Y = -a ln(X) where X is uniformly distributed on [0,1], follows an exponential distribution. Participants are attempting to derive the probability density function (PDF) of Y by utilizing the transformation of variables and the relationship between the PDFs of X and Y. There is confusion regarding the application of the cumulative distribution function (CDF) and the differentiation of the transformation function g(x). The key point is to ensure that the probabilities for corresponding intervals of X and Y are equal. Clarification and detailed calculations are requested to solidify the understanding of the exponential nature of Y.
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Homework Statement



Let X be a uniform random variable in the interval [0,1] i.e., X = U [(0,1)]. Then a new random variable Y is given by Y= g(X), where g(x)= -a. ln(x). Show that Y is exponentially distributed. What is the mean of Y?



Homework Equations



fX(x) = 1/ lambda . exp (-x/ lambda)

0 otherwise


The Attempt at a Solution



Y = g(X) can be computed via FY(y)= Summation 1/ differentiation of g(x) multiplied with Fx(x)
I can't show how this is exponential.

Please help!
 
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so as its constant doesn't f_X(x)=1 in [0,1], zero otherwise

then use the fact that the probabilty for a given interval dx and corresponding interval dy must be the same
|f_X(x)dx| = |f_Y(y)dy|
 
is that what you tried to do? can you show your working?
 
Question: A clock's minute hand has length 4 and its hour hand has length 3. What is the distance between the tips at the moment when it is increasing most rapidly?(Putnam Exam Question) Answer: Making assumption that both the hands moves at constant angular velocities, the answer is ## \sqrt{7} .## But don't you think this assumption is somewhat doubtful and wrong?

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