Uniform Distribution Expected Value

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SUMMARY

The discussion focuses on calculating the expected value E[||X|-2|] for a uniformly distributed random variable X over the interval [-5, 5]. The participants clarify that the probability density function is f(x) = 1 / (10) and the mean is (a+b)/2 = 0. The approach involves changing the variable to y = |X| - 2 and recognizing the need to handle the absolute value through piecewise functions. The final solution requires integrating four distinct pieces derived from the absolute value conditions.

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  • Understanding of uniform distribution and its properties
  • Knowledge of expected value calculations in probability
  • Familiarity with piecewise functions and integration techniques
  • Experience with absolute value functions in mathematical expressions
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  • Learn how to compute expected values for piecewise functions
  • Explore integration techniques for absolute value functions
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Students studying probability and statistics, mathematicians working with random variables, and educators teaching concepts of expected value and uniform distributions.

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Homework Statement


If X~(-5,5) find E[||X|-2|]


Homework Equations


If a variable is distributed uniformly then f(x) = 1 / (b-a), with a mean of (a+b)/2.
If x~u, then y~u.


The Attempt at a Solution


I think I should change the variable, so y = |X| - 2, and then find E[|y|]. So if I do that, I change the integration from -5 and 5 to 3 and 3 because |-5| - 2 = |5| - 2. Wouldn't that just be zero, or do I have my integration points wrong?

I am also confused about finding the expected value of an absolute of something. Should I do two separate integrals, one with integral (-y * f(y) * dy) and the other integral (y * f(y) * dy) or how should I handle the absolute value sign?

I'm pretty confused by this problem, any help would be greatly appreciated!
 
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Try expressing the function piecewise without absolute values. The first step would be:

[tex]||x| - 2| = \begin{cases}<br /> |x| - 2 & \textrm{if } |x| \geq 2 \\<br /> -|x| + 2 & \textrm{otherwise}<br /> \end{cases}[/tex]

Now repeat the procedure for each of the two cases. You will end up with four "pieces" which you can integrate individually and sum the results.
 

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