Final answer:
The terms pdf and cdf represent the probability density function and cumulative distribution function for continuous random variables, crucial for statistical analysis of probabilities.
Step-by-step explanation:
Continuous Probability Functions
The student's question revolves around the concept of probability density functions (pdf) and cumulative distribution functions (cdf) for continuous random variables. A pdf gives us the probability that a continuous random variable falls within a particular range. It is represented by the area under the curve of the function f(x) between two specific points, and the entire area under the curve must equal one, signifying 100% probability over the entire range of X. The cdf is the function that provides the cumulative probability up to a certain point x, essentially the area under the curve from the start of the distribution up to point x. It's critical to understand the difference between pdf and cdf to accurately work with continuous random variables in probability and statistics.