Topics: Random Variable - Probability
Integrating and Deriving
(theorem)
Let be an absolutely continuous random variable with density function . Let be a function.
Let be another random variable with distribution function .
We can obtain , ’s distribution function, by integrating over the region on which . We can then obtain , ’s density function, by deriving this distribution function.
Example
Let and let be given by:
We’ll find by integrating:
Now, notice that is (what we integrated) when . We’ll find the corresponding values for this interval, in terms of by using :
- when
- when
Thus:
Now, we can simply derivate to find the density function:
Variable Change Theorem
(theorem)
Let be an absolutely continuous random variable with values in the interval , and density function .
Let be a strictly increasing or decreasing continuous function with a differentiable inverse.
Then, the random variable takes values in the interval and its density function is: