In probability theory, the law (or formula) of total probability is a fundamental rule relating marginal probabilities to conditional probabilities. It...

The proposition in probability theory known as the law of total expectation, the law of iterated expectations (LIE), Adam's law, the tower rule, and the...

In probability theory, the total variation distance is a distance measure for probability distributions. It is an example of a statistical distance metric...

In probability theory, the law of total variance or variance decomposition formula or conditional variance formulas or law of iterated variances also known...

Bayes' law or Bayes' rule, after Thomas Bayes) gives a mathematical rule for inverting conditional probabilities, allowing us to find the probability of a...

Probability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations...

In mathematics, a probability measure is a real-valued function defined on a set of events in a σ-algebra that satisfies measure properties such as countable...

In probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption...

probability theory and mathematical statistics, the law of total cumulance is a generalization to cumulants of the law of total probability, the law of...

The standard probability axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. These axioms...

The posterior probability is a type of conditional probability that results from updating the prior probability with information summarized by the likelihood...

Cumulative distribution function Law of total cumulance Law of total expectation Law of total probability Law of total variance Almost surely Cox's theorem...

probability theory, the law of large numbers (LLN) is a mathematical law that states that the average of the results obtained from a large number of independent...

In probability theory, the law of total covariance, covariance decomposition formula, or conditional covariance formula states that if X, Y, and Z are...

In probability theory, a probability space or a probability triple ( Ω , F , P ) {\displaystyle (\Omega ,{\mathcal {F}},P)} is a mathematical construct...

In probability theory and statistics, the binomial distribution with parameters n and p is the discrete probability distribution of the number of successes...

In probability and statistics, a realization, observation, or observed value, of a random variable is the value that is actually observed (what actually...

p must also be false. Modus tollens represents an instance of the law of total probability combined with Bayes' theorem expressed as: Pr ( P ) = Pr (...

Probability is the branch of mathematics concerning events and numerical descriptions of how likely they are to occur. The probability of an event is...

In probability theory, an event is a set of outcomes of an experiment (a subset of the sample space) to which a probability is assigned. A single outcome...

process is a stochastic process describing a sequence of possible events in which the probability of each event depends only on the state attained in the...

problems. In statistical theory, the probability distributions of continuous variables can be expressed in terms of probability density functions. In continuous-time...

axioms of probability Boole's inequality Probability interpretations Bayesian probability Frequency probability Conditional probability The law of total probability...

known instance of this observation and includes a distribution on the second digit as well. Newcomb proposed a law that the probability of a single number...

{\displaystyle B} . The probability of the evidence P ( B ) {\displaystyle P(B)} can be calculated using the law of total probability. If { A 1 , A 2 , …...

In probability theory, a tree diagram may be used to represent a probability space. A tree diagram may represent a series of independent events (such...

Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes. Two events are independent, statistically...

In probability theory and related fields, a stochastic (/stəˈkæstɪk/) or random process is a mathematical object usually defined as a family of random...

statistician Law of total covariance Law of total cumulance Law of total expectation Law of total probability Law of total variance Law of truly large...

probability distribution of a random variable which takes the value 1 with probability p {\displaystyle p} and the value 0 with probability q = 1 − p {\displaystyle...