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STAT 372
Longitudinal Data Analysis: Modeling Change over Time Fall 2020
Division III Quantative/Formal Reasoning

Class Details

This course explores modern statistical methods for drawing scientific inferences from longitudinal data, i.e., data collected repeatedly on experimental units over time. The independence assumption made for most classical statistical methods does not hold with this data structure because we have multiple measurements on each individual. Topics will include linear and generalized linear models for correlated data, including marginal and random effect models, as well as computational issues and methods for fitting these models. We will consider many applications in the social and biological sciences.
The Class: Format: lecture; Hybrid format. Approximately 2/3 of class time will be lecture (in person for students who are on campus, recorded for remote students). All synchronous students (whether in person or online) will attend a remote lab/discussion section each week. Asynchronous options will be provided for students unable to participate synchronously.
Limit: 15
Expected: 15
Class#: 2668
Grading: yes pass/fail option, yes fifth course option
Requirements/Evaluation: performance on exams, homework, and a project
Prerequisites: STAT 201 and STAT 346
Enrollment Preferences: junior and senior Statistics majors
Distributions: Division III Quantative/Formal Reasoning
QFR Notes: The course will cover a variety of statistical analysis methods for longitudinal data.
Attributes: PHLH Statistics Courses

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