SOC 321 A: Data Science and Statistics for Social Sciences I

Summer 2024 Full-term
Meeting:
TTh 10:20am - 12:20pm
SLN:
13399
Section Type:
Lecture
Joint Sections:
STAT 321 A , CS&SS 321 A
Instructor:
Syllabus Description (from Canvas):

Welcome to the built-in Syllabus section in Canvas. You may have already noticed that in this template, we've chosen to use a page we titled"Syllabus" to contain our syllabus information. We made this decision because we wanted to be able to have the syllabus as part of a Module, and this built-in section can't be added to Modules.

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Catalog Description:
Introduction to applied data analysis for social scientists. Focuses on using programming to prepare, explore, analyze, and present data that arise in social science research. Data science topics include loading, cleaning, and exploring data, basic visualization, reproducible research practices. Statistical topics include measurement, probability, modeling, assessment of statistical evidence. Lectures intermixed with programming and lab sessions. Course overlaps with: B BUS 301. Offered: jointly with CSSS 321/STAT 321; W.
GE Requirements Met:
Social Sciences (SSc)
Quantitative and Symbolic Reasoning (QSR)
Credits:
5.0
Status:
Active
Last updated:
January 20, 2026 - 11:27 pm