Practical Data Analysis with JMP®

Density Functions

For a continuous random variable X, we'll think about the probability that X lies between two values instead of thinking about X assuming one specific value. In other words, rather than solving for Pr(X = a) we'll solve for Pr(a ≤X< b). Fortunately, the software handles all of the computational issues, but it's helpful to have some basic grounding in the underlying theory.

With continuous random variables, probability values are derived from the specific density function that describes the variable. From the standpoint of data analysis, density functions per se have little direct application. You might want to think of a density function as representing the concentration of probability near different possible values of X.