Difference between revisions of "A-B Testing"
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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. | ||
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Latest revision as of 22:03, 2 September 2021
This article is a stub. You can help us by editing this page and expanding it.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. (Source)
Reference: [1] 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.