Learning objectives
- • Separate prediction from causal effect estimation
- • Explain confounding, selection bias, matching, IVs, diff-in-diff, and uplift
- • Know when an experiment is required instead of offline modeling
Math & Stats
Causal Inference, Uplift, and Experimentation
Prepare for causal questions around confounding, treatment effects, uplift modeling, observational data, and experiment design.
Recommended on day 6100 minutesAdvanced
Interview prompts
- • How would you estimate whether a notification caused higher retention?
- • What is the difference between propensity modeling and uplift modeling?
Prerequisites