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3550 Rackham Building University of Michigan Ann Arbor, MI 48109-1070
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Logistic Regression and Related Techniques
May 3, 2012
Edward Rothman and Kathy Welch
This workshop and the companion (Exploratory Factor Analysis and Related Techniques,May 2, 2012) are designed to help participants a) learn about the logical and statistical basis for a set of techniques and b) learn how to carry out these analysis using IBM/SPSS ® statistical software. This workshop introduces binary logistic regression, ordinal logistic regression, and multinomial logistic regression analysis and similar techniques.
- Instructors
- Ed Rothman is a professor in the department of Statistics at the University of Michigan since 1969. He has extensive experience as a statistical consultant in studies both on and off campus.
Kathy Welch is the primary SAS consultant at CSCAR. Her CSCAR responsibilities include consulting on linear and logistic regression and related techniques.
- Audience
- Researchers in applied fields who may encounter data suitable for multivariate techniques
- Prerequisite
- Introductory statistics, basic experience using SPSS/PASW for Windows recommended.
- Provisions
- Enrollees receive lecture notes, a bibliography, and example computer package commands and output. Morning refreshments provided. Break time for lunch (lunch not provided); many restaurants nearby.
- Dates & Times
- Thursday, May 3, 2012, 9:00 AM - 5:00 PM
- Location
- Modern Languages Building, Room 2001A
- Fees
-
- $180 for University of Michigan affiliated faculty, staff and students
- $400 for others
Registrations on or before April 18, 2012 - $215 for University of Michigan affiliated faculty, staff and students
- $500 for others
Registrations after April 18, 2012 Please make checks payable to CSCAR-University of Michigan, or give the University of Michigan Project/Grant or short code to be billed. Send check to CSCAR, 3550 Rackham Bldg., University of Michigan, 915 E. Washington St., Ann Arbor, MI, 48109-1070.
- Registration
- Call CSCAR at 734-764-7828. Enrollment is limited.