The concept of a probability density function (PDF) is fundamental to the study of probability theory, especially when dealing with continuous random variables. A PDF essentially provides a measure of the likelihood of occurrence of different outcomes in an experiment. In the context of a continuous random variable, the PDF gives us an idea of the probability that the variable will assume a value within a certain range. It is important to note that a continuous random variable can take on any value within a given interval, unlike a discrete random variable that can only assume specific values. In this article, we delve deeper into the concept of PDF and demonstrate how to calculate it for a continuous random variable.