Introduction to Probability for Computing

In the previous chapter, we studied individual continuous random variables. We now move on to discussing multiple random variables, which may or may not be independent of each other. Just as in Chapter 3 we used a joint probability mass function (p.m.f.), we now introduce the continuous counterpart, the joint probability density function (joint p.d.f.). We will use the joint p.d.f. to answer questions about the expected value of one random variable, given some information about the other random variable.