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3550 Rackham Building University of Michigan Ann Arbor, MI 48109-1070
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Regression Analysis
February 20, 22 and 24, 2012
Dave Childers and Kathy Welch
This workshop will provide participants with an overview of commonly used methods in simple and multiple linear regression. There will be both lecture and hands-on computer examples, using SPSS. Topics will include: the basic regression model, model assumptions, interpretation of results, significance testing, interactions between variables and the use and interpretation of dummy variables. Analysis of covariance (ANCOVA) models will also be discussed. Model checking methods, including residual plots, assessment of multicollinearity, and influence plots will also be covered. Several methods for selecting a final model will be discussed.
- Instructors
- Dave Childers is an Statistical Consultant at CSCAR
and consults on topics in Stata and R as well as a variety of other
statistical software packages.
Kathy Welch is a Statistical Consultant and the primary SAS Consultant for CSCAR. - Prerequisite
- A Windows instruction class or equivalent knowledge, a basic statistics course or CSCAR's workshop 'Statistics: A Review'.
- Provisions
- The enrollee will receive lecture notes, a bibliography, and example computer package commands with output. Morning refreshments will be served. Break time for lunch (lunch not provided).
- Dates & Times
- February 20, 22 and 24, 2012, 9:00 AM - 4:00 PM
- Location
- Modern Language Building, Room 2001A
- Fees
-
- $300 for University of Michigan affiliated faculty, staff and students
- $700 for others
Registrations on or before February 6, 2012 - $330 for University of Michigan affiliated faculty, staff and students
- $800 for others
Registrations after February 6, 2012 Please make check payable to CSCAR-University of Michigan, or give the University of Michigan shortcode 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 to 24 participants.