Statistics for Civic Life: Reasoning with Data in Democracy

4 Credits.

This course introduces students from all disciplines to the principles and practices of calculus-based statistics as a tool for understanding civic life. The course integrates foundational concepts from probability theory with statistical inference, emphasizing how probabilistic models underpin the construction of confidence intervals and hypothesis tests. Students develop fluency in describing, interpreting, and critically evaluating quantitative information found in public discourse, including polls, media reports, policy analyses, and scientific studies. Through a combination of theoretical development and hands-on data analysis, students learn to compute and interpret confidence intervals, conduct hypothesis tests, and assess uncertainty using probabilistic reasoning. Real-world case studies are used to connect formal statistical methods to questions arising in democratic society. Students will use R and other relevant software (e.g., Python) to analyze datasets, simulate probabilistic models, and communicate evidence-based conclusions.