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- A [[probability distribution]] is a mathematical approach to quantifying uncertainty. ...discrete values only (typically the positive integers), while [[continuous probability distribution|continuous distributions]] describe variables that can take on arbitrary v6 KB (870 words) - 12:20, 15 November 2007
- ...ns]]. The other main class in basic [[probability theory]] is [[continuous probability distribution|continuous probability distributions]]. ...bers ranging from 0 to 1 and their sum is exactly 1, we have a [[discrete probability distribution]], and each "degree of belief" is called a [[probability]].4 KB (590 words) - 09:17, 26 September 2007
- ...], along with [[discrete probability distribution|discrete]] and [[hybrid probability distribution|hybrid]] ones. A continuous probability distribution is a function that, whren integrated over a set representing an event, give3 KB (390 words) - 07:22, 26 September 2007
- 143 bytes (20 words) - 11:01, 4 September 2009
- 12 bytes (1 word) - 12:34, 13 November 2007
- 12 bytes (1 word) - 07:22, 26 September 2007
- Probability distribution where variables can take on arbitrary values in a continuum.122 bytes (15 words) - 11:04, 4 September 2009
- 12 bytes (1 word) - 09:17, 26 September 2007
- 184 bytes (26 words) - 11:06, 4 September 2009
- {{r|Continuous probability distribution}} {{r|Discrete probability distribution}}670 bytes (76 words) - 07:31, 16 April 2010
- Auto-populated based on [[Special:WhatLinksHere/Continuous probability distribution]]. Needs checking by a human. {{r|Discrete probability distribution}}674 bytes (82 words) - 15:40, 11 January 2010
- The '''entropy''' of a [[probability distribution]] is a number that describes the degree of uncertainty or disorder the dist #Given a [[discrete probability distribution]] function f, the entropy H of the distribution (measured in [[bits]]) is1 KB (232 words) - 07:17, 4 January 2008
- Auto-populated based on [[Special:WhatLinksHere/Discrete probability distribution]]. Needs checking by a human. {{r|Continuous probability distribution}}674 bytes (82 words) - 16:00, 11 January 2010
- 127 bytes (16 words) - 06:34, 4 September 2009
- 12 bytes (1 word) - 11:02, 26 September 2007
- 47 bytes (4 words) - 01:51, 4 January 2009
- Auto-populated based on [[Special:WhatLinksHere/Entropy of a probability distribution]]. Needs checking by a human. {{r|Continuous probability distribution}}549 bytes (67 words) - 16:19, 11 January 2010
Page text matches
- {{r|Continuous probability distribution}} {{r|Discrete probability distribution}}670 bytes (76 words) - 07:31, 16 April 2010
- Auto-populated based on [[Special:WhatLinksHere/Discrete probability distribution]]. Needs checking by a human. {{r|Continuous probability distribution}}674 bytes (82 words) - 16:00, 11 January 2010
- Auto-populated based on [[Special:WhatLinksHere/Continuous probability distribution]]. Needs checking by a human. {{r|Discrete probability distribution}}674 bytes (82 words) - 15:40, 11 January 2010
- Auto-populated based on [[Special:WhatLinksHere/Entropy of a probability distribution]]. Needs checking by a human. {{r|Continuous probability distribution}}549 bytes (67 words) - 16:19, 11 January 2010
- ...ion|exponential distribution]]''' is any member of a class of [[continuous probability distribution|continuous probability distributions]] assigning probability *[[Continuous probability distribution]]1 KB (164 words) - 06:14, 14 September 2013
- ...distribution''' and '''zeta distribution''' refer to a class of [[discrete probability distribution]]s. They have been used to model the distribution of words in words in a t1 KB (168 words) - 16:41, 6 February 2009
- {{r|Continuous probability distribution}} {{r|Discrete probability distribution}}687 bytes (82 words) - 20:38, 11 January 2010
- The '''Poisson distribution''' is any member of a class of [[discrete probability distribution|discrete probability distributions]] named after [[Simeon Denis Poisson]]. *[[Probability distribution]]2 KB (233 words) - 09:15, 14 September 2013
- {{r|Continuous probability distribution}} {{r|Discrete probability distribution}}771 bytes (95 words) - 18:24, 11 January 2010
- {{r|Continuous probability distribution}} {{r|Discrete probability distribution}}812 bytes (100 words) - 20:22, 11 January 2010
- #REDIRECT [[Probability distribution]]38 bytes (3 words) - 00:11, 7 May 2007
- The '''entropy''' of a [[probability distribution]] is a number that describes the degree of uncertainty or disorder the dist #Given a [[discrete probability distribution]] function f, the entropy H of the distribution (measured in [[bits]]) is1 KB (232 words) - 07:17, 4 January 2008
- Probability distribution where variables can take on arbitrary values in a continuum.122 bytes (15 words) - 11:04, 4 September 2009
- {{r|Probability distribution}}575 bytes (70 words) - 07:35, 16 April 2010
- ...], along with [[discrete probability distribution|discrete]] and [[hybrid probability distribution|hybrid]] ones. A continuous probability distribution is a function that, whren integrated over a set representing an event, give3 KB (390 words) - 07:22, 26 September 2007
- a measure of the "lobsideness" of a probability distribution. Positive skewness indicates that the tail of the distribution is more str287 bytes (43 words) - 16:21, 23 May 2009
- a test for comparing a mathematical probability distribution with observed data.117 bytes (14 words) - 05:21, 30 June 2009
- {{r|conditional probability distribution}}223 bytes (23 words) - 14:30, 29 June 2009
- a symmetrical bell-shaped probability distribution representing the frequency of random variations of a quantity from its mean163 bytes (20 words) - 12:25, 1 July 2009
- {{r|Discrete probability distribution}}619 bytes (77 words) - 19:36, 11 January 2010