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DTSTART:20221106T020000
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BEGIN:VEVENT
UID:calendar.2371.events_uoft_date.0@www.statistics.utoronto.ca
CREATED:20230227T174552Z
DESCRIPTION:\nWhen and Where: \nMonday, March 06, 2023 3:30 pm to 4:30 pm
  \n Online \n\nSpeakers \nRina Friedberg \n\nDescription: \nAs companies w
 ork to provide the best possible experience for members, users, and cust
 omers, it is crucial to understand how different people – particularly in
 dividuals from sensitive groups – have different experiences. For example\
 , do women visit our platform less frequently than members of other gender
 s? Or perhaps, are people with disabilities disproportionately affected b
 y a change to our user interface? However, to run these statistical tests
  or form estimates to answer these questions, we need to know sensitive a
 ttributes. When dealing with personal data, privacy techniques should be 
 considered, especially when we are dealing with sensitive groups, e.g. r
 ace/ethnicity or gender. We study a new privacy model where users belong t
 o certain sensitive groups, and we show how to conduct statistical infere
 nce on whether there are significant differences in outcomes between the v
 arious groups. We introduce a general chi-squared test that accounts for d
 ifferential privacy in group membership, and show how this covers a broad
  set of hypothesis tests, improving statistical power over tests that ign
 ore the noise due to privacy. The presentation is based on joint work with
  Ryan Rogers.Please join the event.About Rina FriedbergRina Friedberg is a
  senior data scientist at LinkedIn, specializing in data privacy research
 . She focuses on practical problems in data science, including hypothesis
  testing under differential privacy and quantifying demographic representa
 tion changes in large-scale A/B testing systems. She has previously worked
  in global health statistics, studying clinical trials to evaluate gender
 -based violence prevention programs for adolescents in Nairobi. Friedberg 
 holds a PhD in statistics from Stanford University. \n\nContact Informatio
 n: \n CANSSI Ontario \n\nCategories \n Data Science ARES \n\nAudiences \n 
 FacultyGraduate Students
DTSTART;TZID=America/New_York:20230306T153000
DTEND;TZID=America/New_York:20230306T163000
LAST-MODIFIED:20230227T174719Z
SUMMARY:Private Hypothesis Testing over Sensitive Groups
URL;TYPE=URI:https://www.statistics.utoronto.ca/events/private-hypothesis-t
 esting-over-sensitive-groups
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