AEM 5105

Designing and Conducting Experiments in Firms

Course Description

Course information provided by the 2026-2027 Catalog.

Firms are increasingly drawing on data and experimental methods to serve customers and drive profits. This course will teach managers and business leaders how to design and conduct robust experiments, generate impactful interventions, select appropriate outcomes, and implement proper randomization. Focused primarily on conceptual understanding rather than technical implementation, the course utilizes discussion-based lectures and culminates in a group project in which teams will design and present on an experiment addressing a real business challenge. While students will gain hands-on experience with data via problem sets which solidify course concepts, no advanced software skills are required; the focus is on being able to work closely with data analysts and data scientists.

Prerequisites background equivalent to: AEM 2100.

Forbidden Overlaps AEM 3105, AEM 5105, NBA 6392

Last 4 Terms Offered (None)

Learning Outcomes

• Interpret experimental data - Distinguish correlation from causation and analyze experimental results to evaluate the business implications of findings as well as differential treatment effects across customer segments.
• Evaluate and select appropriate outcome measures and metrics - Select and justify key performance indicators and measurement strategies that align with business objectives while accounting for potential issues such as attrition, censoring, and proxy variables.
• Implement proper randomization and sampling techniques - Apply randomization methods including stratification, clustering, and between vs. within-subject designs while assessing potential complications such as spillovers and non-compliance.
• Assess ethical considerations and stakeholder management in business experiments - Evaluate the ethical implications of proposed experiments and develop strategies for managing stakeholder concerns, public relations risks, and regulatory compliance.
• Synthesize experimental design principles into comprehensive business proposals - Create complete experimental proposals that integrate sampling, treatment design, outcome selection, randomization, and analysis plans to address real business challenges.

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