Independence (probability theory)Independence is a fundamental notion in probability theory, as in statistics and the theory of stochastic processes. Two events are independent, statistically independent, or stochastically independent if, informally speaking, the occurrence of one does not affect the probability of occurrence of the other or, equivalently, does not affect the odds. Similarly, two random variables are independent if the realization of one does not affect the probability distribution of the other.
Probability theoryProbability theory or probability calculus is the branch of mathematics concerned with probability. Although there are several different probability interpretations, probability theory treats the concept in a rigorous mathematical manner by expressing it through a set of axioms. Typically these axioms formalise probability in terms of a probability space, which assigns a measure taking values between 0 and 1, termed the probability measure, to a set of outcomes called the sample space.
ProbabilityProbability is the branch of mathematics concerning numerical descriptions of how likely an event is to occur, or how likely it is that a proposition is true. The probability of an event is a number between 0 and 1, where, roughly speaking, 0 indicates impossibility of the event and 1 indicates certainty. The higher the probability of an event, the more likely it is that the event will occur. A simple example is the tossing of a fair (unbiased) coin.
Probability distributionIn probability theory and statistics, a probability distribution is the mathematical function that gives the probabilities of occurrence of different possible outcomes for an experiment. It is a mathematical description of a random phenomenon in terms of its sample space and the probabilities of events (subsets of the sample space). For instance, if X is used to denote the outcome of a coin toss ("the experiment"), then the probability distribution of X would take the value 0.5 (1 in 2 or 1/2) for X = heads, and 0.
Bayesian probabilityBayesian probability (ˈbeɪziən or ˈbeɪʒən ) is an interpretation of the concept of probability, in which, instead of frequency or propensity of some phenomenon, probability is interpreted as reasonable expectation representing a state of knowledge or as quantification of a personal belief. The Bayesian interpretation of probability can be seen as an extension of propositional logic that enables reasoning with hypotheses; that is, with propositions whose truth or falsity is unknown.
Pairwise independenceIn probability theory, a pairwise independent collection of random variables is a set of random variables any two of which are independent. Any collection of mutually independent random variables is pairwise independent, but some pairwise independent collections are not mutually independent. Pairwise independent random variables with finite variance are uncorrelated. A pair of random variables X and Y are independent if and only if the random vector (X, Y) with joint cumulative distribution function (CDF) satisfies or equivalently, their joint density satisfies That is, the joint distribution is equal to the product of the marginal distributions.
Conditional independenceIn probability theory, conditional independence describes situations wherein an observation is irrelevant or redundant when evaluating the certainty of a hypothesis. Conditional independence is usually formulated in terms of conditional probability, as a special case where the probability of the hypothesis given the uninformative observation is equal to the probability without. If is the hypothesis, and and are observations, conditional independence can be stated as an equality: where is the probability of given both and .
Conditional probabilityIn probability theory, conditional probability is a measure of the probability of an event occurring, given that another event (by assumption, presumption, assertion or evidence) has already occurred. This particular method relies on event B occurring with some sort of relationship with another event A. In this event, the event B can be analyzed by a conditional probability with respect to A. If the event of interest is A and the event B is known or assumed to have occurred, "the conditional probability of A given B", or "the probability of A under the condition B", is usually written as P(AB) or occasionally P_B(A).
Probability axiomsThe Kolmogorov axioms are the foundations of probability theory introduced by Russian mathematician Andrey Kolmogorov in 1933. These axioms remain central and have direct contributions to mathematics, the physical sciences, and real-world probability cases. An alternative approach to formalising probability, favoured by some Bayesians, is given by Cox's theorem. The assumptions as to setting up the axioms can be summarised as follows: Let be a measure space with being the probability of some event , and .
Event (probability theory)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 may be an element of many different events, and different events in an experiment are usually not equally likely, since they may include very different groups of outcomes. An event consisting of only a single outcome is called an or an ; that is, it is a singleton set. An event is said to if contains the outcome of the experiment (or trial) (that is, if ).
Probability interpretationsThe word probability has been used in a variety of ways since it was first applied to the mathematical study of games of chance. Does probability measure the real, physical, tendency of something to occur, or is it a measure of how strongly one believes it will occur, or does it draw on both these elements? In answering such questions, mathematicians interpret the probability values of probability theory. There are two broad categories of probability interpretations which can be called "physical" and "evidential" probabilities.
Thirty Years' WarThe Thirty Years' War was one of the longest and most destructive conflicts in European history, lasting from 1618 to 1648. Fought primarily in Central Europe, an estimated 4.5 to 8 million soldiers and civilians died as a result of battle, famine, and disease, while some areas of what is now modern Germany experienced population declines of over 50%. Related conflicts include the Eighty Years' War, the War of the Mantuan Succession, the Franco-Spanish War, the Dutch-Portuguese War and the Portuguese Restoration War.
Eighty Years' WarThe Eighty Years' War or Dutch Revolt (Nederlandse Opstand) (c. 1566/1568–1648) was an armed conflict in the Habsburg Netherlands between disparate groups of rebels and the Spanish government. The causes of the war included the Reformation, centralisation, taxation, and the rights and privileges of the nobility and cities. After the initial stages, Philip II of Spain, the sovereign of the Netherlands, deployed his armies and regained control over most of the rebel-held territories.
Peppered mothThe peppered moth (Biston betularia) is a temperate species of night-flying moth. It is mostly found in the northern hemisphere in places like Asia, Europe and North America. Peppered moth evolution is an example of population genetics and natural selection. The caterpillars of the peppered moth not only mimic the form but also the colour of a twig. Recent research indicates that the caterpillars can sense the twig's colour with their skin and match their body colour to the background to protect themselves from predators.
Conditional probability distributionIn probability theory and statistics, given two jointly distributed random variables and , the conditional probability distribution of given is the probability distribution of when is known to be a particular value; in some cases the conditional probabilities may be expressed as functions containing the unspecified value of as a parameter. When both and are categorical variables, a conditional probability table is typically used to represent the conditional probability.
Frequentist probabilityFrequentist probability or frequentism is an interpretation of probability; it defines an event's probability as the limit of its relative frequency in many trials (the long-run probability). Probabilities can be found (in principle) by a repeatable objective process (and are thus ideally devoid of opinion). The continued use of frequentist methods in scientific inference, however, has been called into question. The development of the frequentist account was motivated by the problems and paradoxes of the previously dominant viewpoint, the classical interpretation.
Peppered moth evolutionThe evolution of the peppered moth is an evolutionary instance of directional colour change in the moth population as a consequence of air pollution during the Industrial Revolution. The frequency of dark-coloured moths increased at that time, an example of industrial melanism. Later, when pollution was reduced, the light-coloured form again predominated. Industrial melanism in the peppered moth was an early test of Charles Darwin's natural selection in action, and it remains a classic example in the teaching of evolution.
MathematicsMathematics is an area of knowledge that includes the topics of numbers, formulas and related structures, shapes and the spaces in which they are contained, and quantities and their changes. These topics are represented in modern mathematics with the major subdisciplines of number theory, algebra, geometry, and analysis, respectively. There is no general consensus among mathematicians about a common definition for their academic discipline. Most mathematical activity involves the discovery of properties of abstract objects and the use of pure reason to prove them.
Fiscal yearA fiscal year (or financial year, or sometimes budget year) is used in government accounting, which varies between countries, and for budget purposes. It is also used for financial reporting by businesses and other organizations. Laws in many jurisdictions require company financial reports to be prepared and published on an annual basis but generally with the reporting period not aligning with the calendar year (1 January to 31 December).
Year 2038 problemThe year 2038 problem (also known as Y2038, Y2K38, Y2K38 superbug or the Epochalypse) is a time formatting bug in computer systems with representing times after 03:14:07 UTC on 19 January 2038. The problem exists in systems which measure Unix time – the number of seconds elapsed since the Unix epoch (00:00:00 UTC on 1 January 1970) – and store it in a signed 32-bit integer. The data type is only capable of representing integers between −(2^31) and 231 − 1, meaning the latest time that can be properly encoded is 2^31 − 1 seconds after epoch (03:14:07 UTC on 19 January 2038).
