This video will dive into probabilistic analysis using the classic Hiring Problem from the well-known textbook "Introduction to Algorithms" (CLRS). The Hiring Problem models a scenario where you’re interviewing candidates sequentially and want to hire the best one. We’ll explore how probabilistic analysis helps estimate the expected number of hires and decisions you'd make, even though each candidate’s quality is unknown in advance. Then, we will see another example of an algorithm with its worst, best, and expected running time.
