Digital Experiments

Undergraduate / Graduate

This course takes a hands-on approach to help students develop a deep understanding of the theoretical underpinnings, principles, and methodologies of digital experimentation. Students learn how to design robust and ethical digital experiments in various domains (e.g., online behavior, A/B testing, product design, etc.) while mastering tools and platforms for running digital experiments, such as survey platforms, online experiment frameworks, and analytics tools. Key concepts taught in this course include causal inference, experiment types and validity, factorial designs, sampling, blocking, random assignment, stimuli, mediators, moderators, and effect sizes. Class sessions alternate between lectures & workshops and the culmination of the course requires students to apply their newly acquired knowledge of digital experimental design to solve real-world research problems, e.g., in marketing, behavioral economics, and the social sciences more broadly.