Finding Expected Value of a Double-Exponential Distribution

  • Thread starter Thread starter corny1355
  • Start date Start date
  • Tags Tags
    Integration
Click For Summary
SUMMARY

The expected value of a random variable X with a double-exponential distribution, defined by the density function f_x(x) = (1/2)e^(-p|x|), is conclusively 0. This is derived from the integral of the product of x and the density function, specifically ∫ x * f(x) dx. The integral can be evaluated by splitting it into two parts, accounting for both positive and negative values of x, thus confirming that the average value of X is indeed 0.

PREREQUISITES
  • Understanding of double-exponential distribution
  • Knowledge of integral calculus
  • Familiarity with probability density functions
  • Experience with evaluating improper integrals
NEXT STEPS
  • Study the properties of double-exponential distributions
  • Learn techniques for evaluating improper integrals
  • Explore graphical representations of probability density functions
  • Investigate applications of expected value in statistics
USEFUL FOR

Students in statistics or mathematics, data analysts, and anyone studying probability theory who seeks to understand the expected value of distributions.

corny1355
Messages
1
Reaction score
0

Homework Statement



The random variable X has a double-exponential distribution with parameter p>0 if its density is given by

f_x (x) = (1/2)e^(-p|x|) for all x.

Show that the expected value of X = 0.

Homework Equations



I know that the expected value of a random variable x is

∫ x * f(x) dx

The Attempt at a Solution



We are told that f_x (x) = (1/2)e^(-p|x|)

So I'm guessing you have to do the following integral going from 0 to infinity:

∫ x * (1/2)e^(-p|x|) dx

But I'm unsure about how to compute this integral.
 
Last edited:
Physics news on Phys.org
If your sample space is [itex][0,\infty)[/itex], how could the average value of X be 0?
Also, there wouldn't be a need for absolute values if x couldn't be negative.
I`m sure that the problem implicitly assumes that X can take all values in R.

You could evaluate the integral by splitting it in two pieces.
There's a faster way though. Maybe drawing the graph of f will help.
 

Similar threads

  • · Replies 4 ·
Replies
4
Views
2K
  • · Replies 19 ·
Replies
19
Views
4K
Replies
7
Views
1K
  • · Replies 4 ·
Replies
4
Views
2K
Replies
6
Views
2K
Replies
7
Views
2K
  • · Replies 13 ·
Replies
13
Views
2K
  • · Replies 8 ·
Replies
8
Views
2K
  • · Replies 13 ·
Replies
13
Views
13K
Replies
2
Views
2K