Chernoff bound

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Covers test statistics, threshold values, and lower bounds for estimating properties.

Explores sub exponential bounds and Bernstein conditions in verifying sub exponentiality.

Explores Markov's theorem, Chernoff bound, and probability theory fundamentals, including good coloring, 2-colorable graphs, and rare events.

Explores the theory of martingales, including conditional expectations, Chernoff bounds, and Azuma's inequality.

Introduces subgaussian and subexponential random variables, conditional expectation, and Orlicz norms.

Covers Cramer's theorem and Hoeffding's inequality in the context of the large deviations principle.

Covers McDiarmid's inequality, providing concentration bounds for functions of independent random variables.

Explores distribution estimation methods, fitness functions, and the importance of selecting the right estimator for accurate results.

Covers concentration inequalities and sampling methods for estimating unknown distributions, with a focus on population infection rates.

Covers topics on relations, sequences, and summations, including lattices, recurrence relations, and sigma notation.