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| == [[A/B Testing]] == | | == [[A/B Testing]] == |
| 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])
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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.
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| == Adaptive Landscape == | | == Adaptive Landscape == |
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| '''Related Concepts:''' Virtue Signaling, Vice Signaling. | | '''Related Concepts:''' Virtue Signaling, Vice Signaling. |
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| == Wu-Yang Dictionary == | | == [[Wu-Yang Dictionary]] == |
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| {{#widget:Tweet|id=980671434153275393}}
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| * [https://en.wikipedia.org/wiki/Yang_Chen-Ning C. N. Yang on Wikipedia]
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| <!--== The Long Nap == -->
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| <!-- == Freedom is an export == --> | | <!-- == Freedom is an export == --> |
