This course provides students with a foundation in exploring data using the R programming language. Students will learn how to source, manage, transform, and explore a wide variety of data types. Students will also master the fundamental concepts for visualizing and communicating information contained in raw data, including the human psychology of visual information processing. All analyses will be conducted to support reproducibility from raw data to results using RMarkdown. Teaching will involve interactive lectures with plenty of class time spent working on examples and coding. Students will be assessed through in-class quizzes, reading reflections, and exploratory projects. Throughout the semester, students will work on a research project of their own design to demonstrate mastery of the course’s topics. At the end of the semester, students will submit a final, reproducible report of their project along with a 10-minute video presentation of their findings.
Having successfully completed this course, students will be able to:
Students should have taken EMSE 4574: Programming for Analytics or have experience working with data in at least one programming language. If you’re not sure whether you have the necessary prerequisite skills, you can try and get up to speed by completing this optional course prerequisites assignment before class starts. Once class starts, it may be difficult to keep up without this background, and it may be more beneficial to wait and take this course next year after taking Programming for Analytics.