Differences

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--- data_analysis:ab_test [2021/09/18 13:55]
prgram
+++ data_analysis:ab_test [2021/09/30 10:07] (current)
prgram [A/B test]
@@ Line 1: / Line 1: @@
 ====== 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]]
+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.
@@ Line 16: / Line 16: @@
 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
+[[https://cdn2.hubspot.net/hubfs/310840/VWO_SmartStats_technical_whitepaper.pdf|VWO_SmartStats_technical_whitepaper]]
-Sample size calculation for two independent Groups
-https://www.researchgate.net/publication/287927836_Sample_Size_Calculation_for_Two_Independent_Groups_A_Useful_Rule_of_Thumb
+[[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]]
@@ Line 34: / Line 34: @@
   * 가설 : 인터뷰, idea, 기존자료 분석
   * 실험설계 : control/treatment, 지표, bayesian/frequentist
-    * 랜덤 unit : user/session/page
+    * Random unit : user/session/page
-    * 어떻게 : 전체 / segment
+    * Target unit : 전체 / segment
-    * size : sample, traffic 분배
+    * Size : sample, traffic 분배
-    * 얼마나 : 학습효과
+    * How long : 학습효과
-  * 실행 : 모니터링. 오류, 다른 feature들이 떨어지는지, 예상치 못하게 효율이 떨어지는지
+  * 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 : proxy 문제, A/A test->검증
+  * 결정 : 통계적vs실질적 유의도, A/A test->검증
 {{tag>data_analysis 실험 experiment ABtest}}