printer friendly pageSTATS 203: Regression Models and Analysis of Variance
Modeling and interpretation of observational and experimental data using linear and nonlinear regression methods. Model building and selection methods. Multivariable analysis. Fixed and random effects models. Experimental design. Prerequisites:
Math 51,
Math 104,
STATS 200. See
https://statistics.stanford.edu/course-equiv for equivalent courses in other departments that satisfy these prerequisites.
Terms: Aut, Spr
| Units: 3
STATS 203V: Regression Models and Analysis of Variance
Modeling and interpretation of observational and experimental data using linear and nonlinear regression methods. Model building and selection methods. Multivariable analysis. Fixed and random effects models. Experimental design. 203V only: This course is offered remotely only via video segments (MOOC style). TAs will host remote weekly office hours using an online platform such as Zoom. Prerequisites:
STATS 200,
MATH 51,
MATH 104 (recommended)See
https://statistics.stanford.edu/course-equiv for equivalent courses in other departments that satisfy these prerequisites.
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