Course Material
Syllabus
Discussion Papers Background Reading Bayesian Example 1 (JAGS code) (slice sampling) (additional code) Bayesian Example 2 (slice sampling) (additional code) (data) Scraping Example Topics Example 1 Topics Example 2 Supervised Learning Example (additional code) (additional code) Ideal Point Estimation Example Nonparametrics Example Bayesian Notes Text Analysis Slides Machine Learning Notes Ideal Point Estimation Slides Nonparametrics Slides Assignment 1 (data) Assignment 2 Assignment 3 (data) Course ScheduleClass 1 (Jan. 26) - Intro, Bayesian Statistics Class 2 (Feb. 2) - Bayesian Statistics Class 3 (Feb. 9) - Class Canceled, Assignment 1 AssignedClass 4 (Feb. 16) - Bayesian Statistics, Discussion of [1] Quinn et al. (1999) and [2] Jackman (2005) Class 5 (Feb. 23) - Text, Assignment 1 DueClass 6 (Mar. 2) - Text, Unsupervised Learning, Assignment 1 DueClass 7 (Mar. 9) - Discussion of [4] Grimmer (2010) and [5] Quinn et al. (2010), Assignment 2 AssignedClass 8 (Mar. 23) - Supervised Learning, Assignment 2 DueClass 9 (Mar. 30) - Supervised Learning, Discussion of [8] Deiermier et al. (2012), Assignment 2 Assigned
Class 10 (Apr. 6) - Discussion of Misc. PapersClass 11 (Apr. 13) - Discussion of [6] Martin and Yurukoglu (2015), Ideal Point Estimation Class 12 (Apr. 20) - Ideal Point Estimation, Discussion of [13] Clark and Lauderdale (2008), Assignment 3 DueClass 13 (Apr. 27) - Discussion of [15] Bonica (2013), Nonparametrics Class 14 (May 4) - Nonparametrics |