Understanding a Proof Involving Integrals: Explained

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The proof involves the relationship between the expected value of a random variable and integrals. It starts with the expression EX = integral from 0 to infinity of 1 - F(x) dx, which can be rewritten as EX = integral from 0 to infinity of P(X > x) dx. By changing the order of integration, the proof shows that this can also be expressed as an integral involving the probability density function f(y). The discussion emphasizes that the final integral represents the expected value of X, illustrating the equivalence of different integration methods over the same area. Understanding this proof requires recognizing the interchangeability of integration limits and the significance of the region defined by y = x.
jetoso
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I have a problem understanding the following proof:
EX = integral from 0 to infinity of 1 - F(x) dx
Say this integral can be:
EX = integral from 0 to infinity of P(X > x), then
EX = integral from 0 to infinity of integral from x to infinity of f(y)dydx
= integral from 0 to infinity of integral from 0 to y of dxf(y)dy = EX

Can somebody explain me how and why the last integral is included?
Thanks.
 
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jetoso said:
EX = integral from 0 to infinity of integral from x to infinity of f(y)dydx
= integral from 0 to infinity of integral from 0 to y of dxf(y)dy = EX
\int_0^\infty \left(\int_x^\infty f(y)dy\right) dx \overset{?}{=} \int_0^\infty \left(\int_0^y dx\right) f(y)dy

Think of this as integrating the area of the unit square. You could first integrate along the y-axis then integrate that integral along the x axis. Alternatively you could first integrate over x then integrate that over y.

Or suppose you are to integrate function f over the area that lies below the y = x line on the unit square. You can either integrate f from 0 to x on the y-axis then integrate that from 0 to 1 on the x axis. Alternatively you could integrate f from 0 to y on the x-axis then integrate that from 0 to 1 on the y axis.

This isn't an exact or perfect explanation but I hope that it will be useful to some degree.
 
The integral

<br /> \int_0^\infty \left(1-F(x)\right) \, dx<br />

can be rewritten with this step.

<br /> \int_0^\infty \left(1-F(x)\right) \, dx = \int_0^\infty \left(\int_x^\infty f(y)\dy\right) \,dx <br />

The region over which we are integrating is the portion of the first quadrant that is on and to the right of line y = x

This can also be calculated by reversing the order of integration. In this case the inner integral goes from x=0 to x = y. Here is the work all in a single location.

<br /> \begin{align*}<br /> \int_0^\infty \left(1-F(x)\right) \, dx &amp; = \int_0^\infty \left(\int_x^\infty f(y) \,dy\right) \,dx\\<br /> &amp; = \int_0^\infty \left(\int_0^y \, dy \right) f(x) \,dx = \int_0^\infty y f(y) \,dy<br /> \end{align*}<br />

If you remember that the variable names are simply placeholders in this work you realize that the final integral is simply the expected value of X.
 
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