The Borell–TIS (Truncation and Integration for Sums) inequality is a result in probability theory and the theory of Gaussian measures. It provides bounds on the tail probabilities of sums of independent random variables that have a certain structure, particularly in relation to Gaussian distributions. In simple terms, the Borell–TIS inequality helps to quantify how much the sum of independent random variables deviates from its expected value.

Cantelli's inequality is a probabilistic inequality that provides a bound on the probability that a random variable deviates from its mean. Specifically, it is used to measure the tail probabilities of a probability distribution.

The Cheeger bound, also known as Cheeger's inequality, is a result in the field of spectral graph theory and relates the first eigenvalue of the Laplacian of a graph to its Cheeger constant. The Cheeger constant is a measure of a graph's connectivity and is defined in terms of the minimal ratio of the edge cut size to the total vertex weight involved.

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.

Doob's Martingale Inequality is a fundamental result in the theory of martingales, which are stochastic processes that model fair game scenarios. Specifically, Doob's inequality provides bounds on the probabilities related to the maximum of a martingale. There are a couple of versions of Doob's Martingale Inequality, but the most common one deals with a bounded integrable martingale.

Etemadi's inequality is a result in probability theory that provides a bound on the tail probabilities of a non-negative, integrable random variable. Specifically, it is used to give a probabilistic estimate concerning the sum of independent random variables, especially in the context of martingales and stopping times. The inequality states that if \( X \) is a non-negative random variable that is integrable (i.e.

QuantLib is an open-source library for quantitative finance, primarily used for modeling, trading, and risk management in financial markets. It is written in C++ and provides a comprehensive suite of tools for quantitative analysis, including: - **Interest rate models**: Facilities for modeling and analyzing interest rate derivatives. - **Options pricing models**: Various methodologies for pricing different types of options, including European, American, and exotic options.

Gauss's inequality, also known as the Gaussian inequality, is a result in probability theory and statistics that provides a bound on the tail probabilities of a normal distribution. Specifically, it states that for a standard normal variable \( Z \) (mean 0 and variance 1), the probability that \( Z \) deviates from its mean by more than a certain threshold can be bounded.

Hoeffding's inequality is a fundamental result in probability theory and statistics that provides a bound on the probability that the sum of bounded independent random variables deviates from its expected value. It is particularly useful in the context of statistical learning and empirical process theory.

The Janson inequality is a result in probability theory, particularly in the context of the study of random variables and dependent events. It provides a bound on the probability that a sum of random variables exceeds its expected value. Specifically, it is often used when dealing with random variables that exhibit some form of dependence.

The title "University Professor of Natural Philosophy" at Dublin typically refers to a prestigious academic position at Trinity College Dublin. Historically, "natural philosophy" is the term that was used before the modern sciences were fully articulated, encompassing topics like physics, astronomy, and other sciences that study the natural world. The role of the University Professor of Natural Philosophy would generally involve teaching, conducting research, and contributing to the academic community in areas related to the natural sciences.

Multidimensional Chebyshev's inequality is an extension of the classical Chebyshev's inequality to the context of multivariate distributions. The classical Chebyshev's inequality provides a probabilistic bound on how far a random variable can deviate from its mean.

The Van den Berg–Kesten inequality is a result in the field of probability theory, particularly in the study of dependent random variables. It provides a way to compare the probabilities of certain events that are dependent on each other under specific conditions. In a more formal context, the inequality deals with events in a finite set, where these events are allowed to be dependent, and it provides a bound on the probability of the union of these events.

Ville's inequality is a result in probability theory that provides an upper bound on the probability of a certain event involving a martingale. Specifically, it deals with the behavior of a non-negative submartingale and relates to stopping times.

Vitale's random Brunn–Minkowski inequality is a result in the field of geometric probability, particularly in the study of random convex bodies. It generalizes the classical Brunn–Minkowski inequality, which is a fundamental result in the theory of convex sets in Euclidean space, relating the volume of convex bodies to the volumes of their convex combinations.

P-boxes (probability boxes) and probability bounds analysis are powerful tools in the field of uncertainty quantification and risk assessment. They provide a systematic way to characterize and handle uncertainties in various applications, particularly when precise probability distributions are difficult to obtain.

An "appeal to probability" is a type of logical fallacy that occurs when someone assumes that because something is possible or likely, it must be true or will happen. This fallacy involves an unwarranted conclusion based on the probability of an event, rather than on solid evidence or deductive reasoning. For example, someone might argue, "It's likely that it will rain tomorrow, so it will rain.

The Law of Averages is a principle that suggests that over a large enough sample size, events will statistically tend to average out. In other words, it implies that if something happens with a certain probability, over time and numerous trials, the outcomes will reflect that probability.