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These courses may have been taken by previous Social Work students or may have been identified as of possible interest to Social Work students. Some courses may be restricted and/or not open to Social Work students. There are many other courses not listed offered elsewhere in the university that may be of interest. Interest in courses numbered below 500 should be checked for graduate level status since many are only offered for undergraduate credit. You can check this by contacting the department offering the course or contacting the SSW Registrar.

The information may not be up to date or complete. Please seek additional information from the department where the course is offered and from the instructors of the course. We strongly recommend you discuss your plans to take outside courses with your advisor to make sure they are a good fit for your educational program.

Statistics SOC 510

School: Sociology
Credits: 4
Prerequisites: Graduate Standing
Course Description: This course is the first of a two-semester sequence required of all sociology department graduate students. It consists of two weekly class sessions plus a lab-discussion. In the first semester we cover basic concepts of probability, sampling distributions, confidence intervals, and statistical inference. The lab sessions will be used to discuss problems encountered in the lectures and written assignments and to develop statistical computing skills. The course assumes no prior knowledge of statistics and no mathematical knowledge beyond high school algebra. Please note that this is not a course in statistical theory, but rather one on the applied use of statistical methods for the analysis of social science data. As such, it will explore many topics but not deal with any of them in great depth. Those who are contemplating more advanced work involving statistical methods should consider taking other courses that do delve more deeply into statistical theory, of which there are a variety on campus.


SectionInstructorDaysLocationU-M Class #
001Best, Rachel KahnMon, Wed3207 LSA11706
002Eno, Jared PongFri4260 LSA25937

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