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Grinnell College · 4 credits · UGRD

This course introduces core topics in data science using R programming. This includes introductions to getting and cleaning data, data management, exploratory data analysis, reproducible research, and data visualization. This course incorporates case studies from multiple disciplines and emphasizes the importance of properly communicating statistical ideas. Prerequisite: STA-209. Suggested CSC-151 or computer programming experience. STAFF
Fall 2026 · 2 sections
Aug 27 – Dec 18
| Section | Days & time | Location | Instructor |
|---|---|---|---|
| 01Class #98423-STA-230-01 | Monday, Wednesday, Friday 2:10 PM - 3:00 PM Noyce Science Ctr 2401 (Lecture) | Noyce Science Ctr 2401 | Nathan Friedrichsen |
| 01 notes: Develop an informed critical or theoretical perspective on the social impact of data collection, including the social construction of data production, and the use of algorithmic techniques to process that data. | |||
| 02Class #98424-STA-230-02 |
|---|
| Monday, Wednesday, Friday 3:10 PM - 4:00 PM Noyce Science Ctr 2401 (Lecture) |
| Noyce Science Ctr 2401 |
| Nathan Friedrichsen |
| 02 notes: Develop an informed critical or theoretical perspective on the social impact of data collection, including the social construction of data production, and the use of algorithmic techniques to process that data. |