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In mathematics, a set A is a subset of a set B if all elements of A are also elements of B; B is then a superset of A. It is possible for A and B to be equal; if they are unequal, then A is a proper subset of B. The relationship of one set being a subset of another is called inclusion (or sometimes containment).
The elements of a sample space may be numbers, words, letters, or symbols. They can also be finite, countably infinite, or uncountably infinite. [6] A subset of the sample space is an event, denoted by . If the outcome of an experiment is included in , then event has occurred. [7]
The arithmetic mean of a series of values ,, …, is often denoted by placing an "overbar" over the symbol, e.g. ¯, pronounced "bar". Some commonly used symbols for sample statistics are given below: the sample mean ¯,
The expanded definition is the following: a probability space is a triple (,,) consisting of: the sample space Ω {\displaystyle \Omega } – an arbitrary non-empty set , the σ-algebra F ⊆ 2 Ω {\displaystyle {\mathcal {F}}\subseteq 2^{\Omega }} (also called σ-field) – a set of subsets of Ω {\displaystyle \Omega } , called events , such ...
However, the definition of maximal and minimal elements is more general. In particular, a set can have many maximal and minimal elements, whereas infima and suprema are unique. Whereas maxima and minima must be members of the subset that is under consideration, the infimum and supremum of a subset need not be members of that subset themselves.
In probability theory, an event is a subset of outcomes of an experiment (a subset of the sample space) to which a probability is assigned. [1] A single outcome may be an element of many different events, [2] and different events in an experiment are usually not equally likely, since they may include very different groups of outcomes. [3]
Also, in probability, σ-algebras are pivotal in the definition of conditional expectation. In statistics, (sub) σ-algebras are needed for the formal mathematical definition of a sufficient statistic, [3] particularly when the statistic is a function or a random process and the notion of conditional density is not applicable.
A three-dimensional plot of an indicator function, shown over a square two-dimensional domain (set X): the "raised" portion overlays those two-dimensional points which are members of the "indicated" subset (A). In mathematics, an indicator function or a characteristic function of a subset of a set is a function that maps elements of the subset ...