A-B Testing - Revision history

Pyrope at 21:47, 30 July 2025

2025-07-30T21:47:12Z

← Older revision		Revision as of 21:47, 30 July 2025
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	==On Youtube==		==On Youtube==

	Eric mentions '''A/B Testing''' in an appearance on [~~https://youtu.be/XbKXeVOUQYY?t=1532~~ Impact Theory] in the context of adding “differential diagnosis” to our educational toolkit:		Eric mentions '''A/B Testing''' in an appearance on [[If You Want to See How Deep the Mind Can Go, Watch This (YouTube Content)\|Impact Theory]] in the context of adding “differential diagnosis” to our educational toolkit:

	<blockquote>		<blockquote>
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	{{#widget:YouTube\|id=XbKXeVOUQYY\|start=1532}}		{{#widget:YouTube\|id=XbKXeVOUQYY\|start=1532}}

			== Related Pages ==

			* [[If You Want to See How Deep the Mind Can Go, Watch This (YouTube Content)]]


	[[Category:Concepts]]		[[Category:Concepts]]
	[[Category:Psychology]]		[[Category:Psychology]]

Pyrope at 05:17, 31 March 2024

2024-03-31T05:17:55Z

← Older revision		Revision as of 05:17, 31 March 2024
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	==On Youtube==		==On Youtube==

	Eric mentions '''A/B Testing''' in the context of adding “differential diagnosis” to our educational toolkit:		Eric mentions '''A/B Testing''' in an appearance on [https://youtu.be/XbKXeVOUQYY?t=1532 Impact Theory] in the context of adding “differential diagnosis” to our educational toolkit:

	<blockquote>		<blockquote>
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	</blockquote>		</blockquote>

	{{#widget:YouTube\|id=XbKXeVOUQYY\|start=~~1531~~}}		{{#widget:YouTube\|id=XbKXeVOUQYY\|start=1532}}


	[[Category:Concepts]]		[[Category:Concepts]]
	[[Category:Psychology]]		[[Category:Psychology]]

Pyrope at 05:12, 31 March 2024

2024-03-31T05:12:51Z

← Older revision		Revision as of 05:12, 31 March 2024
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	A/B ~~testing (~~also known as ~~bucket testing or~~ split~~-run~~ testing) is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in ~~the field of statistics. A/B testing is a way~~ to compare two versions of a ~~single~~ variable, typically ~~by testing a subject's response~~ to ~~variant~~ A ~~against variant~~ B, ~~and determining~~ which ~~of the two variants is more effective~~. ~~([https:~~/~~/en.m~~.~~wikipedia.org/wiki/A/B_testing Source])~~		'''A/B Testing''', also known as split testing, is a method used in controlled experiments to compare two versions of a variable, typically denoted as A and B. It is commonly employed in fields such as marketing, web design, and user experience research. By randomly assigning participants to either version A or B, researchers can assess which variant performs better based on predefined metrics such as click-through rates, conversion rates, or user engagement. A/B testing allows for data-driven decision-making by providing insights into the effectiveness of changes made to a product or service.

			==On Youtube==

	'''~~Reference:~~''' ~~[https://m.youtube.com/watch?v=XbKXeVOUQYY] Discussed~~ in the context of adding “differential diagnosis” to our ~~educators’~~ toolkit so that teaching ~~disabled educators can learn how~~ to ~~add~~ to better ~~instruct students rather than externalizations the blame for their inadequate methods onto into the students~~.		Eric mentions '''A/B Testing''' in the context of adding “differential diagnosis” to our educational toolkit:

			<blockquote>
			'''Eric:''' "One of the things I believe is that we're not taught subjects in a way that maximally benefits the largest number of learners. We're taught subjects due to the political economy of making these subjects take a very long time, and rewarding the specialty that might have been the career choice of the person teaching it."

			'''Tom:''' "So what teaching method would optimize for the greatest number of learners?"

			'''Eric:''' "Well, first of all, differential diagnosis, like, are you a visual learner or are you an auditory learner?"

			'''Tom:''' "And we now segment them out."

			'''Eric:''' "Right, and, you know, you start to understand—you present several different styles, you know let's do some A/B Testing—like, you go to your optometrist: Is this better like this? Or like this? Right, and so you start to understand somebody's learning style and learning profile."
			</blockquote>

			{{#widget:YouTube\|id=XbKXeVOUQYY\|start=1531}}

	~~{{Stub}}~~

	[[Category:Concepts]]		[[Category:Concepts]]
	[[Category:Psychology]]		[[Category:Psychology]]

Aardvark: Reverted edits by 191.96.106.91 (talk) to last revision by Aardvark

2023-08-22T13:39:12Z

Reverted edits by 191.96.106.91 (talk) to last revision by Aardvark

← Older revision		Revision as of 13:39, 22 August 2023
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	A/B testing (also known as bucket testing or split-run testing) is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject's response to variant A against variant B, and determining which of the two variants is more effective. ([https://en.m.wikipedia.org/wiki/A/B_testing Source])		A/B testing (also known as bucket testing or split-run testing) is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject's response to variant A against variant B, and determining which of the two variants is more effective. ([https://en.m.wikipedia.org/wiki/A/B_testing Source])


			'''Reference:''' [https://m.youtube.com/watch?v=XbKXeVOUQYY] Discussed in the context of adding “differential diagnosis” to our educators’ toolkit so that teaching disabled educators can learn how to add to better instruct students rather than externalizations the blame for their inadequate methods onto into the students.

			{{Stub}}

			[[Category:Concepts]]
			[[Category:Psychology]]

191.96.106.91: 1

2023-08-22T12:12:53Z

← Older revision		Revision as of 12:12, 22 August 2023
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	A/B testing (also known as bucket testing or split-run testing) is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject's response to variant A against variant B, and determining which of the two variants is more effective. ([https://en.m.wikipedia.org/wiki/A/B_testing Source])		A/B testing (also known as bucket testing or split-run testing) is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject's response to variant A against variant B, and determining which of the two variants is more effective. ([https://en.m.wikipedia.org/wiki/A/B_testing Source])


	'''Reference:''' [https://m.youtube.com/watch?v=XbKXeVOUQYY] Discussed in the context of adding “differential diagnosis” to our educators’ toolkit so that teaching disabled educators can learn how to add to better instruct students rather than externalizations the blame for their inadequate methods onto into the students.

	~~{{Stub}}~~

	~~[[Category:Concepts]]~~
	~~[[Category:Psychology]]~~

Aardvark at 21:12, 14 May 2023

2023-05-14T21:12:19Z

← Older revision		Revision as of 21:12, 14 May 2023
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	~~{{Stub}}~~
	A/B testing (also known as bucket testing or split-run testing) is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject's response to variant A against variant B, and determining which of the two variants is more effective. ([https://en.m.wikipedia.org/wiki/A/B_testing Source])		A/B testing (also known as bucket testing or split-run testing) is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject's response to variant A against variant B, and determining which of the two variants is more effective. ([https://en.m.wikipedia.org/wiki/A/B_testing Source])


	'''Reference:''' [https://m.youtube.com/watch?v=XbKXeVOUQYY] Discussed in the context of adding “differential diagnosis” to our educators’ toolkit so that teaching disabled educators can learn how to add to better instruct students rather than externalizations the blame for their inadequate methods onto into the students.		'''Reference:''' [https://m.youtube.com/watch?v=XbKXeVOUQYY] Discussed in the context of adding “differential diagnosis” to our educators’ toolkit so that teaching disabled educators can learn how to add to better instruct students rather than externalizations the blame for their inadequate methods onto into the students.

			{{Stub}}

	[[Category:Concepts]]		[[Category:Concepts]]
	[[Category:Psychology]]		[[Category:Psychology]]

Pyrope at 22:03, 2 September 2021

2021-09-02T22:03:36Z

← Older revision		Revision as of 22:03, 2 September 2021
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	'''Reference:''' [https://m.youtube.com/watch?v=XbKXeVOUQYY] Discussed in the context of adding “differential diagnosis” to our educators’ toolkit so that teaching disabled educators can learn how to add to better instruct students rather than externalizations the blame for their inadequate methods onto into the students.		'''Reference:''' [https://m.youtube.com/watch?v=XbKXeVOUQYY] Discussed in the context of adding “differential diagnosis” to our educators’ toolkit so that teaching disabled educators can learn how to add to better instruct students rather than externalizations the blame for their inadequate methods onto into the students.

	[[~~category~~:~~Ericisms~~]]		[[Category:Concepts]]
	[[Category:Psychology]]		[[Category:Psychology]]

BeefSandwich27: BeefSandwich27 moved page A/B Testing to A-B Testing

2021-05-10T19:44:30Z

BeefSandwich27 moved page A/B Testing to A-B Testing

← Older revision	Revision as of 19:44, 10 May 2021
(No difference)

Aardvark at 00:06, 14 February 2021

2021-02-14T00:06:35Z

← Older revision		Revision as of 00:06, 14 February 2021
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	[[category:Ericisms]]		[[category:Ericisms]]
			[[Category:Psychology]]

Aardvark at 21:44, 1 February 2021

2021-02-01T21:44:51Z

← Older revision		Revision as of 21:44, 1 February 2021
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			{{Stub}}
	A/B testing (also known as bucket testing or split-run testing) is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject's response to variant A against variant B, and determining which of the two variants is more effective. ([https://en.m.wikipedia.org/wiki/A/B_testing Source])		A/B testing (also known as bucket testing or split-run testing) is a user experience research methodology. A/B tests consist of a randomized experiment with two variants, A and B. It includes application of statistical hypothesis testing or "two-sample hypothesis testing" as used in the field of statistics. A/B testing is a way to compare two versions of a single variable, typically by testing a subject's response to variant A against variant B, and determining which of the two variants is more effective. ([https://en.m.wikipedia.org/wiki/A/B_testing Source])