Syllabus

Introduction

• Barfort, Sebastian. “Getting Started”

• Barfort, Sebastian. “A Few Tips for Coding”

• The Scientist: Get With the Program
• Roger Peng: Data Types

R basics

• Barfort, Sebastian. “Just Enough To Be Dangerous”

• Barfort, Sebastian. “Reading And Working With Data”

• Jennifer Bryan: R basics

• Roger Peng: Reading/Writing Data: Part 1 and 2

Data Visualization

• Wickham, Hadley. 2010. “A Layered Grammar of Graphics”. Journal of Computational and Graphical Statistics, Volume 19, Number 1, Pages 3–28.

• Kahle, David and Hadley Wickham. 2013.'’ggmap: Spatial Visualization with ggplot2’’, The R Journal, 5(1).

• Gelman, Andrew. 2013. '’Choices in statistical graphics: My stories’’. Slides from presentation at New York Data Visualization Meetup.

• Gelman, Andrew and Antony Unwin. 2012. '’Infovis and Statistical Graphics: Different Goals, Different Looks’’.

Data Manipulation

• Watch this introduction to the dplyr package by Hadley Wickham

• Read the dplyr documentation here

• Wickham, Hadley. 2011. “The Split-Apply-Combine Strategy for Data Analysis”. Journal of Statistical Software 40(1)

• Wickham, Hadley. 2014. “Tidy Data”. Journal of Statistical Software 59(10). The R Journal. 2(2): 38-40.

Git & Github

• Zach Jones: Git & Github tutorial

• Carlisle Rainey: Git for Political Science

• Hadley Wickham: Git and GitHub

Big Data

• Einav and Levin: Economics in the Age of Big Data. Science. 2013. Link

• Einav and Levin: The Data Revolution and Economic Analysis. Innovation Policy and the Economy. 2014. Link

• Varian. Big Data: New Tricks for Econometrics. Journal of Economic Perspectives. 2014. Link

Statistical Learning

• Angrist and Pischke: Mastering ‘Metrics. Princeton University Press. 2015. (pages: XI-XV, 1-14)

• James, Witten, Hastie and Tibshirani: Elements of Statistical Learning, Springer Texts in Statistics. (pages: 15-42, 175-184, 214-227)

• Kleinberg, Ludwig, Mullainathan and Obermeyer: Prediction Policy Problems. American Economic Review: Papers & Proceedings. 2015.

• Breiman: Statistical Modeling: The Two Cultures. Statistical Science. 2001.

Text as Data

• Wickham, Hadley. 2010. ‘‘stringr: modern, consistent string processing’’.

• Grimmer. Text as Data: The Promise and Pitfalls of Automatic Content Analysis Methods for Political Texts. Political Analysis. 2013.

Privacy & Ethics

• Ori Heffetz and Katrina Ligett. 2014. Privacy and Data-Based Research. Journal of Economic Perspectives. here or here

• Sections 1 and 4 in Acquisti, Alessandro, Curtis R. Taylor, and Liad Wagman. 2015. The economics of privacy. Available here.

• Neuhaus, Fabian, and Timothy Webmoor. Agile ethics for massified research and visualization. Information, Communication & Society 15.1 (2012): 43-65. Download here

• Web Scraping: A Journalist’s Guide
• On the Ethics of Web Scraping and Data Journalism