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DTSTART:19700308T020000
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DTSTART;TZID=America/Chicago:20261106T110000
DTEND;TZID=America/Chicago:20261106T120000
DTSTAMP:20261003T205601Z
SUMMARY:Statistics and Data Science Seminar Series: "Categorical distance correlation: Concepts\, properties and applications"
UID:647057@northwestern.edu
TZID:America/Chicago
DESCRIPTION:Categorical distance correlation: Concepts\, properties and applications  Qingyang Zhang\, Associate Professor of Mathematical Sciences\, University of Arkansas  Abstract: In this talk\, I will introduce categorical distance correlation (CDC)\, a simple yet powerful statistical functional for assessing dependence in categorical data. After highlighting its empirical power advantages over the traditional Chi-squared test\, I will present key theoretical properties of CDC. These include its B-robustness for fixed or diverging numbers of categories\, its asymptotic distributions under both null and alternative hypotheses\, and the sure screening properties of the maximum likelihood and unbiased estimators. I will also demonstrate its practical utility through an application to General Social Survey data. Time permitting\, I will discuss two extensions\, including CDC under general encodings (such as one-hot encoding for nominal variables and semi-circle encoding for ordinal variables) and a privacy-preserving framework for CDC.\n\nMore Info: https://statistics.northwestern.edu/events/seminars/fall-seminars.html
LOCATION:Chambers Hall\, Ruan Conference Room – lower level\, 600 Foster St\, Evanston\, IL 60208
TRANSP:OPAQUE
URL:https://statistics.northwestern.edu/events/seminars/fall-seminars.html
CREATED:20220914T050000Z
STATUS:CONFIRMED
LAST-MODIFIED:20260930T192645Z
PRIORITY:0
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