Causal Inference and Experimentation [CLICK HERE FOR MORE INFO.]

• • This course provides conceptual understandings and a selection of tools of from the rapidly developing science of causal inference and experimentation. It covers basic conceptual questions like what is causality, and what is causal identification. It also presents a formal system for expressing and understanding causal relationships, with perspectives and tools synergized from multiple disciplines, including statistics (Robin causal model), computer science (causal graph) and econometrics. Finally, it provides an overview of the techniques used to measure causal relationships, ranging from traditional techniques such as Fisher's exact p-value to recent developments such as causal machine learning.

  • The [syllabus of 2021] is here.

Marketing Strategy Research [CLICK HERE FOR MORE INFO.]

• • The course focuses on quantitative aspects of marketing research and how using quantitative tools can help managers address substantive marketing problems such as new product design, market segmentation and positioning. It covers essential tools such as regression (moderation and mediation), conjoint analysis, cluster analysis and multi-dimensional scaling.

  • The [syllabus of 2020] is here.