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.


Share your answers below

You will receive feedback from your instructor and TA directly on this page. Other students are welcome to comment/discuss/point out mistakes/ask questions too!


Answer 1

Firstly, to find the constant k, we can integrate the PDF from negative infinity to positive infinity. The result should equal 1.

$ \int_{-\infty}^{\infty} \! f_X(x) \, \mathrm{d}x = 1. $

However, since the limits of the function don't extend all the way out to infinity, we can simply use the lower limit of a and upper limit of b.

$ => \int_{a}^{b} \! k \, \mathrm{d}x = 1. $

$ => x*k|_a^b = 1 $

$ => k = \frac{1}{(b-a)} $

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) $

Putting in our value for k, we get:

$ = \frac{1}{2(b-a)}(b^2-a^2) $


Answer 2

Write it here

Answer 3

Write it here.


Back to ECE302 Spring 2013 Prof. Boutin

Back to ECE302

Alumni Liaison

Recent Math PhD now doing a post-doctorate at UC Riverside.

Kuei-Nuan Lin