Studying Social Inequality with Data Science
  • Syllabus
  • Team
  • Schedule
  • Office Hours
  • Ed Discussion
  • Forms
  1. Home
  • Home
  • Topics
    • Welcome!
    • Population Sampling
    • Working with Data
      • R and RStudio
      • Visualization
      • Data transformation
      • Weights
      • Statistical Learning
      • Learning Exercise
      • Sample Splitting
    • Describing Inequality
      • Economic opportunity
      • Race
      • Gender
      • Class
    • Asking Questions
    • Reducing Inequality
      • Moral Arugments
      • Causal Interventions
  • Assignments
    • Problem Sets
      • Problem Set 0
      • Problem Set 1
      • Problem Set 2
      • Problem Set 3
      • Problem Set 4
      • Problem Set 5
    • Project
      • Discussion 3-21

Studying Social Inequality with Data Science

Cornell INFO 3370 / 5371 (Spring ’24)

Together, we will generate new knowledge about social inequality using the tools of data science

Learning goals

As a result of participating in this course, students will be able to

  • visualize economic inequality with graphs that summarize survey data
  • connect theories about inequality to quantitative empirical evidence
  • evaluate the effects of hypothetical interventions to reduce inequality
  • conduct data analysis using the R programming language
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