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PRODID:-//ITS Advanced Research Computing - ECPv5.1.5//NONSGML v1.0//EN
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METHOD:PUBLISH
X-WR-CALNAME:ITS Advanced Research Computing
X-ORIGINAL-URL:https://arc.umich.edu
X-WR-CALDESC:Events for ITS Advanced Research Computing
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TZID:America/Detroit
BEGIN:DAYLIGHT
TZOFFSETFROM:-0500
TZOFFSETTO:-0400
TZNAME:EDT
DTSTART:20190310T070000
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TZOFFSETFROM:-0400
TZOFFSETTO:-0500
TZNAME:EST
DTSTART:20191103T060000
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BEGIN:VEVENT
DTSTART;TZID=America/Detroit:20190129T140000
DTEND;TZID=America/Detroit:20190129T160000
DTSTAMP:20220818T014844
CREATED:20190114T175855Z
LAST-MODIFIED:20190118T140104Z
UID:48387-1548770400-1548777600@arc.umich.edu
SUMMARY:Regression analysis with Generalized Linear Models in Python
DESCRIPTION:This workshop will cover fitting generalized linear models (GLMs) in Python\, using the Statsmodels package. We will cover logistic regression\, but the majority of the time we will focus on other GLMs including Poisson\, negative binomial\, and gamma regression. We will provide an overview of the underlying foundation for GLMs\, focusing on the mean/variance relationship and the link function. Participants should have familiarity with linear regression and (ideally) with logistic regression\, but prior exposure to other GLMs is not required. \nParticipants should bring a laptop if they want to work with the examples during the presentation\, but this is optional.
URL:https://arc.umich.edu/event/regression-analysis-with-generalized-linear-models-in-python/
LOCATION:Rackham Building\, Earl Lewis Room\, 3rd Floor East\, 915 E. Washington St.\, Ann Arbor\, MI\, 48109\, United States
CATEGORIES:Workshops
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