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DTSTART:20241103T020000
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DTSTART:20240310T020000
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UID:calendar.3301.events_uoft_date.0@www.statistics.utoronto.ca
CREATED:20240617T144355Z
DESCRIPTION:\nWhen and Where: \nFriday, October 04, 2024 12:00 pm to 1:00
  pm \n\nSpeakers \nSean Taylor \n\nDescription: \nI will discuss leveragin
 g causal discovery in product analytics to uncover new insights and improv
 e product development. First, I introduce a framework for categorizing ca
 usal questions, highlighting common challenges in product analytics, and
  emphasizing the need for discovering new causes that drive outcomes. I wi
 ll present a process for generating hypotheses about causal relationships 
 that are likely to lead to successful ideas for product improvements that 
 can be validated through experiments. The key methodological insight is to
  model event data before they are aggregated, which helps us isolate caus
 al relationships between events and allows for bias reduction to be automa
 ted under certain assumptions.Please join the event. Everyone is welcome—i
 t is free and you do not need to be affiliated with the university.About S
 ean TaylorSean Taylor is a data scientist, social scientist, statisticia
 n, and software developer. He mostly specializes in methods for solving c
 ausal inference and business decision problems, and is particularly inter
 ested in building tools for practitioners working on real-world problems. 
 He is a co-founder and chief scientist at Motif. \n\nContact Information: 
 \n Toronto Data Workshop \n\nCategories \n Seminar SeriesToronto Data Work
 shopWorkshops & Training \n\nAudiences \n FacultyGraduate Students
DTSTART;TZID=America/New_York:20241004T120000
DTEND;TZID=America/New_York:20241004T130000
LAST-MODIFIED:20240927T121104Z
SUMMARY:Casual Discovery for Product Analytics
URL;TYPE=URI:https://www.statistics.utoronto.ca/events/casual-discovery-pro
 duct-analytics
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