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- In mathematical probability equations, a constant (or function) used to ensure that the sum of all prob160 bytes (22 words) - 13:20, 2 January 2009
- The human brain's observed inability to make intuitive estimates of the probability of an event, even when presented with all of the relevant evidence186 bytes (27 words) - 16:18, 27 June 2010
- 12 bytes (1 word) - 12:34, 13 November 2007
- Function of a discrete random variable yielding the probability that the variable will have a given value.143 bytes (20 words) - 11:01, 4 September 2009
- a mathematical expression that defines the probability of occurrence of every possible value of a random variable.150 bytes (20 words) - 02:25, 10 February 2010
- 81 bytes (10 words) - 06:30, 1 May 2010
- | pagename = Conditional probability | abc = probability, Conditional2 KB (227 words) - 07:19, 15 March 2024
- ...[[probability theory]] is [[continuous probability distribution|continuous probability distributions]]. ==Intro - probability as logic viewpoint==4 KB (590 words) - 09:17, 26 September 2007
- ...], along with [[discrete probability distribution|discrete]] and [[hybrid probability distribution|hybrid]] ones. ...on partitions of the set of propositions, in practice intervals in R. The probability assigned to an interval around f.i. 1.7 meters should thus be much larger t3 KB (390 words) - 07:22, 26 September 2007
- Is the probability that a given event occurs given the knowledge of some partial information a165 bytes (24 words) - 01:02, 18 February 2009
- | pagename = Probability space | abc = Probability space2 KB (276 words) - 16:19, 17 October 2009
- 12 bytes (1 word) - 07:22, 26 September 2007
- 12 bytes (1 word) - 09:17, 26 September 2007
- | pagename = Conditioning (probability)2 KB (225 words) - 14:08, 29 June 2009
- | pagename = Normalisation (probability) | abc = Normalisation (probability)709 bytes (60 words) - 13:27, 2 January 2009
- 12 bytes (1 word) - 13:20, 2 January 2009
- '''Circular error probability''' is the most common metric of the accuracy to which a weapon can be deliv2 KB (321 words) - 07:28, 18 March 2024
- 146 bytes (15 words) - 14:17, 29 June 2009
- 133 bytes (18 words) - 06:48, 4 January 2010
- 12 bytes (1 word) - 16:53, 21 September 2008
Page text matches
- #REDIRECT [[Probability distribution]]38 bytes (3 words) - 00:11, 7 May 2007
- #REDIRECT [[Probability space]]31 bytes (3 words) - 13:15, 15 May 2010
- ...distribution''' and '''zeta distribution''' refer to a class of [[discrete probability distribution]]s. They have been used to model the distribution of words in The Zipf distribution with parameter ''n'' assigns probability proportional to 1/''r'' to an integer ''r'' ≤ ''n'' and zero otherwise,1 KB (168 words) - 16:41, 6 February 2009
- ...' is any member of a class of [[discrete probability distribution|discrete probability distributions]] named after [[Simeon Denis Poisson]]. ...But for some reason, no matter how recent or long ago last event was, the probability that another event will occur within the next hour is exactly the same (say2 KB (233 words) - 09:15, 14 September 2013
- {{r|Continuous probability distribution}} {{r|Discrete probability distribution}}687 bytes (82 words) - 20:38, 11 January 2010
- #REDIRECT [[Talk:Normalisation (probability)]]46 bytes (4 words) - 13:20, 2 January 2009
- {{r|Probability theory}}61 bytes (6 words) - 19:25, 23 October 2009
- #REDIRECT [[Circular error probability]]40 bytes (4 words) - 16:55, 21 September 2008
- The '''entropy''' of a [[probability distribution]] is a number that describes the degree of uncertainty or diso #Given a [[discrete probability distribution]] function f, the entropy H of the distribution (measured in1 KB (232 words) - 07:17, 4 January 2008
- | pagename = Probability | abc = Probability689 bytes (60 words) - 06:07, 15 March 2024
- {{r|Probability}} {{r|Conditioning (probability)}}1 KB (158 words) - 20:38, 26 January 2011
- {{r|Probability theory}} {{r|Probability}}164 bytes (19 words) - 16:18, 7 July 2010
- ...ut a function whose argument takes on a particular value according to some probability [[measure]] (a measure that takes on the value 1 over the largest set on wh Let <math>(\Omega,\mathcal{F},P)</math> be an arbitrary [[measure space|probability space]] and <math>(\Omega',\mathcal{F}')</math> an arbitrary [[measurable s2 KB (383 words) - 17:06, 17 October 2007
- <!-- Text is transcluded from the Probability blindness/definition subpage-->90 bytes (11 words) - 16:19, 27 June 2010
- | pagename = Normalisation (probability) | abc = Normalisation (probability)709 bytes (60 words) - 13:27, 2 January 2009
- Conditional probability of exposure to a treatment given observed covariates.113 bytes (13 words) - 13:02, 22 November 2011
- Probability distribution where variables can take on arbitrary values in a continuum.122 bytes (15 words) - 11:04, 4 September 2009
- ...is OK with me, but "A range (of a random variable) that — with a specified probability — contains the true value" is not. There is no such notion "the true valu383 bytes (62 words) - 23:33, 29 June 2009
- {{r|Probability theory}} {{r|Probability distribution}}575 bytes (70 words) - 07:35, 16 April 2010
- ...ion of a domain, scheme, etc. Perhaps this page should be "normalization (probability)", or would "normalized (function)" be better?[[User:Barry R. Smith|Barry R :Normalisation (probability) seems right. [[User:Richard Pinch|Richard Pinch]] 20:26, 21 December 2008514 bytes (61 words) - 13:20, 2 January 2009