SOC 6020

SOC 6020

Course information provided by the Courses of Study 2015-2016.

This course provides an in-depth examination of linear modeling. We begin with the basics of linear regression, including estimation, statistical inference, and model assumptions. We then review several tools for diagnosing violations of statistical assumptions and what to do when things go wrong, including dealing with outliers, missing data, omitted variables, and weights. Finally, we will explore extensions of the linear regression model, including models for categorical outcomes and hierarchical linear modeling. While statistical modeling is the focus of the course, we proceed with the assumption that models are only as good as the theoretical and substantive knowledge behind them. Thus, in covering the technical material, we will spend considerable time discussing the link between substantive knowledge and statistical practice. The course is designed primarily for graduate students in sociology.

When Offered Spring.

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Enrollment Information
Syllabi: none
  •   Regular Academic Session.  Choose one seminar and one discussion. Combined with: PAM 6820

  • 4 Credits Stdnt Opt

  •  7114SOC 6020  SEM 101

  •  9041SOC 6020  DIS 201