POL 676: Statistical Analysis of Big Data (Spring 2017)

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 Schedule
Class 1 (Jan. 26) - Intro, Bayesian Statistics
Class 2 (Feb. 2) - Bayesian Statistics Class 3 (Feb. 9) - Class Canceled, Assignment 1 Assigned
Class 4 (Feb. 16) - Bayesian Statistics, Discussion of [1] Quinn et al. (1999) and [2] Jackman (2005)
Class 5 (Feb. 23) - Text, Assignment 1 Due
Class 6 (Mar. 2) - Text, Unsupervised Learning, Assignment 1 Due
Class 7 (Mar. 9) - Discussion of [4] Grimmer (2010) and [5] Quinn et al. (2010), Assignment 2 Assigned
Class 8 (Mar. 23) - Supervised Learning, Assignment 2 Due
Class 9 (Mar. 30) - Supervised Learning, Discussion of [8] Deiermier et al. (2012), Assignment 2 Assigned
Class 10 (Apr. 6) - Discussion of Misc. Papers
Class 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 Due
Class 13 (Apr. 27) - Discussion of [15] Bonica (2013), Nonparametrics
Class 14 (May 4) - Nonparametrics