data_analysis:ab_test

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data_analysis:ab_test [2021/02/07 05:56] – created prgramdata_analysis:ab_test [2025/07/07 14:12] (current) – external edit 127.0.0.1
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-====== ab test ======+====== A/B test ====== 
 + 
 +AB 테스트 추천 도서 : [[https://www.amazon.com/Trustworthy-Online-Controlled-Experiments-Practical/dp/1108724264|Trustworthy Online Controlled Experiments: A Practical Guide to A/B Testing]] [[https://coupa.ng/b7Omnt|쿠팡]] 
 +통계적 지식 뿐 아니라 실제 적용에서 고민해야할 문제들에 대한 상세한 설명이 있다. 
 + 
 + 
 +[[data_analysis:convergence_testing]]
  
 https://reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/ https://reflectivedata.com/comprehensive-guide-to-statistics-in-a-b-testing/
-https://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf 
 https://www.slideshare.net/cojette/ab-150118831 https://www.slideshare.net/cojette/ab-150118831
 https://onlinemix.tistory.com/entry/significant-result-from-ab-testing https://onlinemix.tistory.com/entry/significant-result-from-ab-testing
-https://is.muni.cz/th/wt0tu/Humaj-thesis.pdf 
 https://cxl.com/blog/ab-testing-guide/ https://cxl.com/blog/ab-testing-guide/
 https://hbr.org/2017/06/a-refresher-on-ab-testing https://hbr.org/2017/06/a-refresher-on-ab-testing
  
 +Bayesian
 +https://is.muni.cz/th/wt0tu/Humaj-thesis.pdf
 +https://brunch.co.kr/@gimmesilver/15
 +[[https://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf|VWO_SmartStats_technical_whitepaper]]
 +
 +
 +[[https://www.researchgate.net/publication/287927836_Sample_Size_Calculation_for_Two_Independent_Groups_A_Useful_Rule_of_Thumb|Sample size calculation for two independent Groups]]
 +
 +
 +https://www.evanmiller.org/ab-testing/
 +
 +
 +MAB
 +http://sanghyukchun.github.io/96/
 +https://kw94.tistory.com/49
 +https://sumniya.tistory.com/9
 +
 +
 +===== 실행순서 ====
 +  * 가설 : 인터뷰, idea, 기존자료 분석
 +  * 실험설계 : control/treatment, 지표, bayesian/frequentist
 +    * Random unit : user/session/page
 +    * Target unit : 전체 / segment
 +    * Size : sample, traffic 분배
 +    * How long : 학습효과
 +  * 실행 : 모니터링. 오류, 다른 feature들이 떨어지는지, 예상치 못하게 효율이 떨어지는지 (cf. 가드레일 metric)
 +  * 분석 : traffic 분배 정합성, 샘플수, 다른 segments의 특성, 다른 지표, Bot은 없는지
 +  * 결정 : 통계적vs실질적 유의도, A/A test->검증
  
 {{tag>data_analysis 실험 experiment ABtest}} {{tag>data_analysis 실험 experiment ABtest}}
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