Social Data Science
  • Syllabus
  • Calendar
  • Problem Sets
    • Problem Set 1: Code Basics
  • Piazza
  • Honors Section
    • Welcome
    • Asking questions with data
    • Accessing data
    • Preparing data
    • Sketching a visualization
    • Writing
    • Presenting orally
  • Extension Requests
  • Past Year Sites
  1. Welcome to the Honors Section
  • Home
  • Getting Started
    • Research Questions in Social Data Science
    • Software Prerequisites
    • Basics of R
    • Visualizing a Distribution
    • Summary Statistics
    • Population Sampling
    • Confidence Intervals
  • Models for Subgroup Summaries
    • Linear Regression
    • Logistic Regression
    • Forests
    • Data-Driven Estimator Selection
    • Are Complex Models Better?
  • Causal Inference with Measured Confounding
    • Defining Causal Effects
    • Exchangeability
    • Directed Acyclic Graphs
    • Matching
    • Models for Causal Inference
  • Causal Inference with Unmeasured Confounding
    • Difference in Difference
    • Regression Discontinuity
    • Instrumental Variables

On this page

  • Our goal
  • What comes next

Welcome to the Honors Section

See the honors section syllabus.

Any student enrolled in Soc 114 is welcome to enroll in the honors section (Soc 189 Sem 3). The honors section is graded as a separate 1.0 credit course. It is an opportunity to engage in a small creative research project and interact with the professor and peers in a seminar format.

Our goal

Our goal in the honors section is to:

  • create our own social science questions
  • download actual data relevant to the questions
  • use the tools of data science to produce answers
  • present findings orally and in writing

What comes next

  • Week 1: Discuss how to ask good research questions and access data
  • Week 2–3: Prepare data with a guided activity using tidyverse tools
  • Week 4: Plan a possible visualization by drawing a sketch
  • Week 5–6: In-class work to produce your visualization
  • Week 7: Practice how to write results
  • Week 8: Plan to present findings
  • Week 9–10: Presentations in class
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