Bayesian probabilityBayesian probability ( or ) 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.
ProbabilityProbability concerns events and numerical descriptions of how likely they are to occur. The probability of an event is a number between 0 and 1; the larger the probability, the more likely an event is to occur. This number is often expressed as a percentage (%), ranging from 0% to 100%. A simple example is the tossing of a fair (unbiased) coin.
Classical definition of probabilityThe classical definition of probability or classical interpretation of probability is identified with the works of Jacob Bernoulli and Pierre-Simon Laplace: The probability of an event is the ratio of the number of cases favorable to it, to the number of all cases possible when nothing leads us to expect that any one of these cases should occur more than any other, which renders them, for us, equally possible.
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.
Experiment (probability theory)In probability theory, an experiment or trial (see below) is the mathematical model of any procedure that can be infinitely repeated and has a well-defined set of possible outcomes, known as the sample space. An experiment is said to be random if it has more than one possible outcome, and deterministic if it has only one. A random experiment that has exactly two (mutually exclusive) possible outcomes is known as a Bernoulli trial.Empirical probabilityIn probability theory and statistics, the empirical probability or experimental probability of an event is an estimate of the probability of the event occurring. A common estimator for the empirical probability is the relative frequency, calculated as the ratio of the number of recorded event outcomes to the total number of trials. It is produced by means not of a theoretical sample space but of an empirical sample.
Pierre-Simon LaplacePierre-Simon, Marquis de Laplace (; French: [pjɛʁ simɔ̃ laplas]; 23 March 1749 – 5 March 1827) was a French polymath, a scholar whose work has been instrumental in the fields of physics, astronomy, mathematics, engineering, statistics, and philosophy. He summarized and extended the work of his predecessors in his five-volume Mécanique céleste (Celestial Mechanics) (1799–1825).
Principle of indifferenceThe principle of indifference (also called principle of insufficient reason) is a rule for assigning epistemic probabilities. The principle of indifference states that in the absence of any relevant evidence, agents should distribute their credence (or "degrees of belief") equally among all the possible outcomes under consideration. It can be viewed as an application of the principle of parsimony and as a special case of the principle of maximum entropy.
Sampling (statistics)In statistics, quality assurance, and survey methodology, sampling is the selection of a subset of individuals from within a statistical population to estimate characteristics of the whole population. The subset, called a statistical sample (or sample, for short), is meant to reflect the whole population, and statisticians attempt to collect samples that are representative of the population.
AristotleAristotle (Ancient Greek: Ἀριστοτέλης, romanized: Aristotélēs; 384–322 BC) was an ancient Greek philosopher and polymath. His writings span the natural sciences, philosophy, linguistics, economics, politics, psychology, and the arts. As the founder of the Peripatetic school of philosophy in the Lyceum in Athens, he began the wider Aristotelian tradition that followed, which set the groundwork for the development of modern science.
Limit of a sequenceIn mathematics, the limit of a sequence is the value that the terms of a sequence "tend to", and is often denoted using the lim{\displaystyle \lim } symbol (e.g., limn→∞an{\displaystyle \lim _{n\to \infty }a_{n}}). If such a limit exists and is finite, the sequence is called convergent. A sequence that does not converge is said to be divergent. The limit of a sequence is said to be the fundamental notion on which the whole of mathematical analysis ultimately rests.
Statistical populationIn statistics, a population is a set of similar items which is of interest for some question or experiment. A statistical population can be a group of existing objects (e.g. the set of all stars within the Milky Way galaxy) or a hypothetical and potentially infinite group of objects conceived as a generalization from experience (e.g. the set of all possible hands in a game of poker).*As an Amazon Associate I earn from qualifying purchases.