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===Answer 1===
 
===Answer 1===
Write it here
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The mean of a random variable is defined as:
 +
 
 +
<math>
 +
\int \! x*f_X(x) \, \mathrm{d}x.
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</math>
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 +
Since the probability density function is k on the interval a to b and zero everywhere else, we can simply write:
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 +
<math>
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=> \int_a^b \! x*k \, \mathrm{d}x.
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</math>
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Thus solving we get
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<math>
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= 1/2x^2k|_a^b
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</math>
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<math>
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= \frac{k}{2}(b^2-a^2)
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</math>
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===Answer 2===
 
===Answer 2===
 
Write it here
 
Write it here

Revision as of 14:33, 22 March 2013

Practice Problem: normalizing the probability mass function of a continuous random variable


A random variable X has the following probability density function:

$ f_X (x) = \left\{ \begin{array}{ll} k, & \text{ if } a\leq x \leq b,\\ 0, & \text{ else}, \end{array} \right. $

where k is a constant. Compute the mean of X.


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Answer 1

The mean of a random variable is defined as:

$ \int \! x*f_X(x) \, \mathrm{d}x. $

Since the probability density function is k on the interval a to b and zero everywhere else, we can simply write:

$ => \int_a^b \! x*k \, \mathrm{d}x. $

Thus solving we get

$ = 1/2x^2k|_a^b $


$ = \frac{k}{2}(b^2-a^2) $

Answer 2

Write it here

Answer 3

Write it here.


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