Y576 : Political Data Analysis II (Linear Regression Model)
A continuation of the graduate sequence in political science, this class begins with multivariate regression, its assumptions and violations before moving on to models of limited dependent variables (binary, count, duration, etc.), measurement models, and handling complex data structures. Emphasis will be on the interpretation and presentation of substantive results using R. Pre-requisite: PS Y575 or permission of the instructor. Students will be asked to produce an original piece of research that will be presented in a public poster session at the end of the semester.
Semester(s) Offered: Spring
Class time: Thursday : 2:30-4:30
Instructor: Chris DeSante - email@example.com
Other Contact(s): Chris DeSante - firstname.lastname@example.org
Prerequisites: introductory statistics, high school algebra
Algebra Required?: Yes for notation, proofs, homework
Calculus Required?: concepts used, but not required
Recommended follow-up classes: S503, Y577
Substantive Orientation: Social Sciences
Statistical Orientation: Applied Statistics, Computational Statistics
Books used: None required.
Applied/Theoretical: This is mostly an applied course, but the applications and programming problems will be driven by statistical theory. Students will be expected to present either an original research study or a replication of a published paper at the end of the semester.
Software Used: R
How the software is used: R and R studio will be used to write code for statistical algorithms
Presentations: Students will be required to present an original research study or replication of a published study
Keywords: computational statistics, statistical programming, econometrics, regression