Speaker(s): Madeleine Thompson

Everyone wants to know what caused what. But most attempts to determine causality from observed data are ineffective in ways that surprise people. This session covers running experiments, observational data, internal validity, external validity, and controlling for confounding factors. You will learn how to do this analysis visually in Tableau, because causal analysis is a domain where automated tools often don't work, and human understanding of the situation is a requirement.

Topic: Data Science and Statistics
Theme: Data and Analytics Skills
Type: Session
Level: Intermediate
Role: Analyst
Track: Analytics
Time: Friday - 2:15pm to 3:16pm

Recording and Materials