PSCI 107 900
This course will primarily meet asynchronously
This course introduces students to techniques for acquiring, analyzing, and visualizing big data using the free statistics program R. Although this is not a statistics course, students will learn basic principles of probability and statistics, such as hypothesis testing, simple linear regression, and experiments. Data science is best learned through practice, so this course focuses on real-world applications. In addition to weekly problem sets, students will complete two small research projects: one using publicly available data, and another in which students will design and run their own survey. Leaving this course, students will be able to obtain data in a wide variety of formats, test hypotheses using that data, and visualize and present their findings. This course uses examples and exercises from political science, but the techniques are applicable to many settings, including other social sciences, business, education, natural sciences, the humanities, and more. No background in statistics, computing, or political science is required. No textbook purchase is required for this course. Students must have access to a computer on which they can install R, RStudio, Zoom, and Slack (free downloads). This course fulfills the School of Arts & Sciences Quantitative Data Analysis requirement.
Subject Area Vocab