Expected value of the log of a uniform distribution

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To calculate the expected value of the log of a uniform distribution, the integral of ln(x) over the interval [0, 1] is used. The correct formula for the expected value E[X] is derived from the uniform distribution's properties. The initial attempt using a.ln(a) was incorrect, leading to an erroneous result of -1/4 instead of the expected -1. The proper method involves integrating ln(x) with the uniform distribution's density function, confirming that this approach yields the correct expected value and variance. The discussion emphasizes the importance of using the right integration technique for accurate results.
Gekko
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Homework Statement



How to calculate the expected value of the log of a uniform distribution?

Homework Equations



E[X] where X=ln(U(0,1))

The Attempt at a Solution



integral from 0 to 1 of a.ln(a) da where a = U(0,1)
= -1/4

However I know the answer is -1
 
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Why do you integrate over a \cdot ln(a)?
 
Yes, that's not right I see.

I used this approach instead. To find the first moment of a uniform distribution it is:

1/(b-a) * integral from a to b of x

In this case it is

1/(b-a) * integral from a to b of ln(x)

Is this ok?

This approach calculates the correct value for expected value and variance
 
Last edited:
Yup, that's the correct method.
 
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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