 Chernoff bound

For every $\lambda >0$, Markov inequality applied to $e^{\lambda X}$ givesOptimizing over $\lambda$ gives the Chernoff bound in terms of the moment-generating function of $X$.

The Chernoff bound is a probabilistic technique used to provide exponentially decreasing bounds on the tail distributions of sums of independent random variables. It is particularly useful in the analysis of algorithms and in fields like theoretical computer science, statistics, and information theory. ### Overview: The Chernoff bound gives us a way to quantify how unlikely it is for the sum of independent random variables to deviate significantly from its expected value.