Brad Carlin's U of M School of Public Health course offerings

Here are the courses I am teaching during the 2013-14 school year:

PubH 6400-102, Topics in Hierarchical Bayesian Analysis
Summer 2014, Mon-Tues-Wed-Fri June 9-13, 1:00 - 5:00 pm, Mayo C381.

Textbook: Bayesian Methods for Data Analysis, 3rd ed., ISBN 978-1-58488-697-6,
by B.P. Carlin and T.A. Louis, Chapman and Hall/CRC Press, Boca Raton, FL, 2009.

The course's Moodle site contains the course materials; click and be ready with your U of M x500 ID and password

This is a 1-credit, 1-week intensive experience in Bayesian methods that does NOT assume any background in calculus. It would be ideal for data managers and others who see and seek to make sense of complex data every day, but who are not "biostatisticians" per se. Both traditional college credit and continuing education (CE) credits are available.

Besides being a useful 4-day semitechnical short course in the core elements of Bayesian methods, this course also serves as a "capstone" experience for the new University of Minnesota School of Public Health Certificate in Applied Biostatistics, and is taught as part of the U of M SPH Summer Public Health Institute (PHI). The class meets during the third week of this program, and can be taken concurrently with another PHI course in the afternoons, yielding a total of 2 course credits for this one week alone. The other 13 credits required for the Certificate can be obtained in either face-to-face or online learning environments. Thus, if the latter option is selected, the entire Certificate can be completed with just one week in residence at the University of Minnesota (in early June, when the weather is always very pleasant and both indoor and outdoor social activities are plentiful). Feel free to contact me for more information!


PubH 8403, Research Skills in Biostatistics
Fall 2013, Wed 2:30-3:20 pm, Mayo A434 (the Mayo 4 Biostat conference room).

Textbook: none, but handouts and other materials provided as needed

This is a 1 credit course that introduces doctoral students in Biostatistics to research skills necessary for writing and defending a dissertation, and more generally for a career in research. Prequisites are Stat 8101-02 and admission to the PhD program in Biostatistics, or instructor's consent. The course is meant to be taken the fall before the PhD written exam is to be attempted, so "Schedule 2" students would typically wait to enroll until their second year in the program.

Grading is S/N only.


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