Section 01: MWF 8:30-9:20am, Lab on Mondays 1:30-4:20pm, TA Claire Powell
Section 03: MWF 11:30am-12:20pm, Lab on Wednesdays 1:30-4:20pm, TA Milo Dao
Dr. Ladd’s Student Drop-In Hours: W 9:30-11am, Th 1-3pm in Burton Morgan 411
TA Hours (for all DA 101 TAs) are posted online here.
Many of the most pressing problems in the world can be addressed with data. We are awash in data, and modern citizenship demands that we become literate in how to interpret data, what assumptions and processes are necessary to analyze data, as well as how we might participate in generating our own analyses and presentations of data. Consequently, data analytics is an emerging field with skills applicable to a wide variety of disciplines. This course introduces analysis, computation, and presentation concerns through the investigation of data driven puzzles in a wide array of fields – political, economic, historical, social, biological, and others. No previous coding or statistics experience is required.
At the end of this course, you should be able to:
- identify, describe, and use different formats of data and data sources
- collect, clean, store, and extract data needed for an analysis
- write basic computer programs using RStudio for a reproducible data analysis workflow
- create data visualizations and interpret them
- perform statistical analysis on a dataset, and interpret the results
- evaluate the ethical, social, and legal issues in data collection, analysis, and security
- combine the above to communicate and interpret all aspects of data analysis (data, cleaning, analysis, results) to a diverse, technical or non-technical audience, in oral, visual, and written format