Markov's inequality

Markov's inequality provides a way to estimate the likelihood that a non-negative random variable exceeds a certain threshold. It states that the probability of the variable exceeding a particular value is at most the expected value of the variable divided by that threshold. In simpler terms, if you know the average outcome, you can bound the chance that an individual outcome is very large. This helps in risk assessment and in understanding the tail behavior of distributions without knowing their full details.