Uniform Distribution Expected Value

In summary, to find the expected value of ||X|-2| when X~(-5,5), we need to change the variable to y = |X| - 2 and express the function piecewise without absolute values. This leads to four individual integrals, which can be summed together to find the overall expected value.
  • #1
redskins187
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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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  • #2
Try expressing the function piecewise without absolute values. The first step would be:

[tex]||x| - 2| = \begin{cases}
|x| - 2 & \textrm{if } |x| \geq 2 \\
-|x| + 2 & \textrm{otherwise}
\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.
 

Related to Uniform Distribution Expected Value

What is Uniform Distribution Expected Value?

Uniform Distribution Expected Value is a statistical concept that represents the average value that is expected to occur in a uniform distribution. This means that in a uniform distribution, all possible outcomes have an equal chance of occurring, and the expected value is the midpoint of the range of values.

How do you calculate the Uniform Distribution Expected Value?

The formula for calculating Uniform Distribution Expected Value is (a + b) / 2, where a and b are the minimum and maximum values in the distribution. This essentially finds the midpoint of the range of values and represents the expected average.

What is the significance of Uniform Distribution Expected Value?

Uniform Distribution Expected Value is an important concept in statistics as it provides a measure of central tendency in a uniform distribution. It allows us to understand the average value of a set of data that follows a uniform distribution, which can help in making predictions and decisions based on the data.

Can the Uniform Distribution Expected Value be negative?

No, the Uniform Distribution Expected Value cannot be negative. This is because the expected value is calculated by finding the midpoint of the range of values, and in a uniform distribution, all values have an equal chance of occurring, so the midpoint will always be a positive value.

How does the Uniform Distribution Expected Value differ from other measures of central tendency?

The Uniform Distribution Expected Value differs from other measures of central tendency, such as mean, median, and mode, because it is specifically used for data that follows a uniform distribution. Other measures of central tendency are used for different types of distributions, and they may provide different values and interpretations.

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