An in-depth exploration of applied linear regression analysis. Covers characteristics of estimates, such as unbiasedness and efficiency. Encourages fluency with the theoretical issues involved in the basic linear regression using simple algebra, familiarity with the general model using matrix algebra, and fluency with the computer application of multivariate regressions and the probit/logit models.

Prerequisite: CCJS620. Credit only granted for: CCJS498F or CCJS621. Formerly: CCJS498F
Credits: 3
Grading Method: Regular, Pass-Fail, Audit

Course Offerings

    Spring 2020Instructor: Laura Dugan