• About this course
  • Office Hours
  • 1 Introduction to Statistical Learning
    • 1.1 Seminar
      • 1.1.1 Exercise
      • 1.1.2 Exercise
      • 1.1.3 Exercise
    • 1.2 Solutions
      • 1.2.1 Exercise
      • 1.2.2 Exercise
      • 1.2.3 Exercise
  • 2 Linear Regression
    • 2.1 Seminar
      • 2.1.1 Exercise
      • 2.1.2 Exercise
      • 2.1.3 Exercise
      • 2.1.4 Optional Exercise
    • 2.2 Solutions
      • 2.2.1 Exercise
      • 2.2.2 Exercise
      • 2.2.3 Exercise
      • 2.2.4 Optional Exercise
  • 3 Classification
    • 3.1 Seminar
      • 3.1.1 Exercise
      • 3.1.2 Exercise
      • 3.1.3 Exercise
    • 3.2 Solutions
      • 3.2.1 Exercise
      • 3.2.2 Exercise
      • 3.2.3 Exercise
  • 4 Resampling Methods and Model Selection
    • 4.1 Seminar
      • 4.1.1 Exercise
      • 4.1.2 Exercise
      • 4.1.3 Exercise
    • 4.2 Solutions
      • 4.2.1 Exercise
      • 4.2.2 Exercise
      • 4.2.3 Exercise
  • 5 Nonlinear Models and Tree-based Methods
    • 5.1 Seminar
      • 5.1.1 Exercise
      • 5.1.2 Exercise
      • 5.1.3 Exercise
    • 5.2 Solutions
      • 5.2.1 Exercise
      • 5.2.2 Exercise
      • 5.2.3 Exercise
  • 6 SVMs and Unsupervised Learning
    • 6.1 Seminar
      • 6.1.1 Exercise
      • 6.1.2 Exercise
    • 6.2 Solutions
      • 6.2.1 Exercise
      • 6.2.2 Exercise
  • 7 Vector Space Models & Text Classification
    • 7.1 Seminar
      • 7.1.1 Exercise
  • 8 Word Embeddings
    • 8.1 Seminar
      • 8.1.1 Exercise
      • 8.1.2 Running GloVe
  • 9 Topic Models
    • 9.1 Seminar
      • 9.1.1 Exercise
  • 10 Review Session
    • 10.1 Seminar
  • Datathons
    • R Presentation structure
    • Submission
    • What we are looking for
    • Datathon 1
      • Groups
      • Dataset
    • Datathon 2
      • Groups
      • Dataset
    • Datathon 3
      • Groups
      • Dataset
      • Loading UNGD Corpus in R
  • Text Analysis
    • Wordscores
      • Plotting with rworldmap
      • Plotting with ggplot
    • Structural Topic Models
    • Document Similarity
  • Tutorials
  • Resources
    • Downloading R and RStudio
    • Online Learning
    • Graphics and Visualizations
    • Documentation
    • Other Resources
    • R Humor
  • Datasets
    • R Packages
    • Governmental and Nongovernmental Organizations
    • Collections
    • Books
    • World Bank DataBank

Advanced Quantitative Methods

Datasets

R Packages

  • R Datasets Package

Governmental and Nongovernmental Organizations

  • Centers for Disease Control and Prevention
  • IMF
  • OECD
  • UK Data Service
  • US Data.gov
  • World Bank
  • Polity Project

Collections

  • Consortium of European Social Science Data Archives
  • Datahub
  • Harvard Dataverse
  • ICPSR at University of Michigan
  • StatSci.org
  • UC Irvine
  • UK Data Archive

Books

  • An Introduction to Statistical Learning
  • Econometric Analysis
  • Introduction to Econometrics