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440:. For example, if one were to toss the same coin one hundred times and record each result, each toss would be considered a trial within the experiment composed of all hundred tosses.
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is defined in such a way that, if the experiment were to be repeated an infinite number of times, the relative frequencies of occurrence of each of the events would
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When an experiment is conducted, one (and only one) outcome results— although this outcome may be included in any number of
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is the result of a single execution of the model. Since individual outcomes might be of little practical use, more complicated
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This article is about the probabilistic model used in actual experiments. For a discussion about actual experiments, see
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As a simple experiment, we may flip a coin twice. The sample space (where the order of the two flips is relevant) is
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which occurs when a "heads" occurs in either of the two flips. This event contains all of the outcomes except
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Random experiments are often conducted repeatedly, so that the collective results may be subjected to
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of the various outcomes and events that can occur in the experiment and apply the methods of
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are used to characterize groups of outcomes. The collection of all such events is a
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A random experiment is described or modeled by a mathematical construct known as a
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Procedure that can be infinitely repeated, with a well-defined set of outcomes
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A mathematical description of an experiment consists of three parts:
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where "H" means "heads" and "T" means "tails". Note that each of
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if it has only one. A random experiment that has exactly two (
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727:"Trial, Experiment, Event, Result/Outcome - Probability"
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Probability, Random
Variables, and Stochastic Processes
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680:"Listing All Possible Outcomes (The Sample Space)"
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705:Papoulis, Athanasios (1984). "Bernoulli Trials".
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682:. Bowling Green State University. Archived from
580:Once an experiment is designed and established,
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603:{\displaystyle \scriptstyle {\mathcal {F}}}
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281:Law of total probability
276:Conditional independence
165:Exponential distribution
150:Probability distribution
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155:Bernoulli distribution
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160:Binomial distribution
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286:Law of large numbers
255:Marginal probability
180:Poisson distribution
29:Part of a series on
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686:on 16 October 2000
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715:. pp. 57–63.
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312:Tree diagram
307:Venn diagram
271:Independence
217:Markov chain
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101:Sample space
713:McGraw-Hill
227:Random walk
68:Determinism
56:Probability
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573:function,
368:infinitely
356:experiment
138:Experiment
85:Randomness
31:statistics
21:experiment
484:A set of
364:procedure
131:Singleton
771:Category
690:June 25,
653:See also
639:outcomes
620:approach
479:outcomes
469:, Ω (or
379:outcomes
212:Variance
736:22 July
530:outcome
126:Outcome
647:(T, T)
534:events
486:events
438:trials
410:events
388:random
73:System
61:Axioms
643:event
360:trial
354:, an
106:Event
738:2013
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375:set
358:or
350:In
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624:P
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612:ω
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481:.
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332:t
325:v
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