Binomial distribution - Revision history

imported>Doug Williamson: Add link.

2020-11-27T00:29:43Z

Add link.

← Older revision		Revision as of 00:29, 27 November 2020
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	* [[Binomial]]		* [[Binomial]]
	* [[Discrete random variable]]		* [[Discrete random variable]]
			* [[Distribution]]
	* [[Frequency distribution]]		* [[Frequency distribution]]
	* [[Poisson distribution]]		* [[Poisson distribution]]

	[[Category:The_business_context]]		[[Category:The_business_context]]

imported>Doug Williamson: Categorise.

2018-03-21T14:01:35Z

Categorise.

← Older revision		Revision as of 14:01, 21 March 2018
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	* [[Frequency distribution]]		* [[Frequency distribution]]
	* [[Poisson distribution]]		* [[Poisson distribution]]

			[[Category:The_business_context]]

imported>Doug Williamson: Link with Binary page.

2018-01-14T20:18:07Z

Link with Binary page.

← Older revision		Revision as of 20:18, 14 January 2018
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	== See also ==		== See also ==
			* [[Binary]]
	* [[Binomial]]		* [[Binomial]]
	* [[Discrete random variable]]		* [[Discrete random variable]]
	* [[Frequency distribution]]		* [[Frequency distribution]]
	* [[Poisson distribution]]		* [[Poisson distribution]]

imported>Doug Williamson: Amend from 'useful' model to 'appropriate'.

2014-08-07T11:19:44Z

Amend from 'useful' model to 'appropriate'.

← Older revision		Revision as of 11:19, 7 August 2014
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	The binomial distribution can be ~~a useful~~ model for processes where:		The binomial distribution can be an appropriate model for processes where:

	#The process consists of a limited whole number of identical trials or situations (n).		#The process consists of a limited whole number of identical trials or situations (n).

imported>Doug Williamson: Add 'limited' before 'whole number' to differentiate from Poisson distribution.

2014-08-07T11:03:06Z

Add 'limited' before 'whole number' to differentiate from Poisson distribution.

← Older revision		Revision as of 11:03, 7 August 2014
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	The binomial distribution can be a useful model for processes where:		The binomial distribution can be a useful model for processes where:

	#The process consists of a whole number of identical trials or situations (n).		#The process consists of a limited whole number of identical trials or situations (n).
	#Each trial results in just one of only two possible outcomes (eg success or failure).		#Each trial results in just one of only two possible outcomes (eg success or failure).
	#The probability of success (p) remains constant for each trial.		#The probability of success (p) remains constant for each trial.

imported>Doug Williamson: Punctuation added

2014-08-05T14:16:54Z

Punctuation added

← Older revision		Revision as of 14:16, 5 August 2014
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	#Each trial results in just one of only two possible outcomes (eg success or failure).		#Each trial results in just one of only two possible outcomes (eg success or failure).
	#The probability of success (p) remains constant for each trial.		#The probability of success (p) remains constant for each trial.
	#The trials are independent and		#The trials are independent, and
	#Primary interest lies in the probability of a specified number of successes (or of failures) in the n trials.		#Primary interest lies in the probability of a specified number of successes (or of failures) in the n trials.

imported>Doug Williamson: Add example from ACT ESA exam, April 2014, Q7.

2014-08-05T14:08:08Z

Add example from ACT ESA exam, April 2014, Q7.

← Older revision		Revision as of 14:08, 5 August 2014
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	#The trials are independent and		#The trials are independent and
	#Primary interest lies in the probability of a specified number of successes (or of failures) in the n trials.		#Primary interest lies in the probability of a specified number of successes (or of failures) in the n trials.


			For example, the total number of sales achieved in a fixed number of sales appointments, assuming the probability of achieving a sale remains constant for each appointment.

imported>Doug Williamson: Align with Glossary and link with Poisson distribution page.

2014-08-05T13:48:11Z

Align with Glossary and link with Poisson distribution page.

← Older revision		Revision as of 13:48, 5 August 2014
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	''Statistics.''		''Statistics.''

	A discrete probability distribution ~~that applies when an experiment is conducted ''~~n~~'' times with each~~ trial ~~having a~~ probability ~~''p''~~ of success ~~and~~ each trial is independent of ~~every other trial~~.		A discrete probability distribution built up from a series of binomial trials.


			The binomial distribution can be a useful model for processes where:

			#The process consists of a whole number of identical trials or situations (n).
			#Each trial results in just one of only two possible outcomes (eg success or failure).
			#The probability of success (p) remains constant for each trial.
			#The trials are independent and
			#Primary interest lies in the probability of a specified number of successes (or of failures) in the n trials.


	== See also ==		== See also ==
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	* [[Discrete random variable]]		* [[Discrete random variable]]
	* [[Frequency distribution]]		* [[Frequency distribution]]
			* [[Poisson distribution]]

imported>Doug Williamson: Spacing

2013-08-01T19:06:11Z

Spacing

← Older revision		Revision as of 19:06, 1 August 2013
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	''Statistics.''		''Statistics.''

	A discrete probability distribution that applies when an experiment is conducted ''n'' times with each trial having a probability ''p'' of success and each trial is independent of every other trial.		A discrete probability distribution that applies when an experiment is conducted ''n'' times with each trial having a probability ''p'' of success and each trial is independent of every other trial.

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	* [[Discrete random variable]]		* [[Discrete random variable]]
	* [[Frequency distribution]]		* [[Frequency distribution]]

imported>Administrator: CSV import

2012-10-23T14:10:43Z

CSV import

New page

''Statistics.''
A discrete probability distribution that applies when an experiment is conducted ''n'' times with each trial having a probability ''p'' of success and each trial is independent of every other trial.

== See also ==
* [[Binomial]]
* [[Discrete random variable]]
* [[Frequency distribution]]