Accelerated Analysis of Sociological Data

Description from DukeHub

This course is for students who intend to pursue graduate education in social science or want to develop strong data science skills. Covers quantitative techniques common to sociological science and allied fields, including testing competing scientific explanations, descriptive and inferential statistics, exploratory data analysis, regression, and data visualization. Includes elements of data science workflows, such as coding in R, literate programming with Quarto, and version control using git. Satisfies statistics requirement for sociology majors. Not open to students who have taken SOCIOL 333.

Skills

• programmingdescription: "coding" and 1 more
• data and statisticsdescription: "data science" and 8 more

AI-resilient: 0 of 5 0/5

• No: Physical, lab or field work
• No: Live work with people
• No: Judgment someone is accountable for
• No: A craft you practice with your hands or body
• No: Small, in-person format

The checks lean on Microsoft Research, Working with AI (2025), which found generative AI applies least to physical work and hands-on work with people. A signal, not a promise. How the score works

More in SOCIOL

• Seeing Through Society: Thinking Like a Sociologist SOCIOL 110CC
• Beyond the School-to-Prison Pipeline: Families Under Surveillance SOCIOL 138CN
• Society, the Self, and the Natural World SOCIOL 180S
• Sex, Gender, and Society SOCIOL 218
• Incarceration Nation SOCIOL 228
• Elite Deviance: White Collar, Corporate, and Governmental Misconduct SOCIOL 244

All SOCIOL courses · All of Graduate School