Department: Engineering Management and Systems Engineering @ GWU

Credits: 3


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.

Learning Objectives:

Having successfully completed this course, students will be able to:

  • Write a clear, focused, concise, complex, and arguable research question.
  • Import, manipulate, clean, visualize, and export data in R.
  • Wrangle data from its original format into a fit-for-purpose format.
  • Conduct a systematic exploratory data analysis (EDA) of different types of data.
  • Apply fundamental principles of visualizing information for exploratory analysis and communication.
  • Get data off the web and expose data, code, results on the web.
  • Generate fully reproducible reports that contain code, equations, visualizations, and narrative text.


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.

EMSE 4575: Exploratory Data Analysis (Spring 2021)
Wednesdays | 12:45 - 3:15 PM | Dr. John Paul Helveston | |