ATE
Average treatment effect: the average difference between what happens under treatment and what would have happened under control.
DoOperator Research
Glossary
Short definitions for the terms that show up across the chapters.
AIPW
Augmented inverse probability weighting: an estimator that combines an outcome model with a propensity model.
Bandit
A repeated decision problem where the learner balances exploring options with exploiting the best-known option.
Collider
A variable caused by two other variables; conditioning on it can create a spurious association.
Confounder
A variable that affects both the treatment and the outcome, making naive comparisons biased.
Counterfactual
The outcome that would have happened under a different action or treatment.
CUPED
A variance-reduction method that uses pre-experiment measurements to make randomized experiments more precise.
DAG
Directed acyclic graph: a diagram of causal assumptions using arrows and no cycles.
E-value
A sensitivity metric: how strong unmeasured confounding would need to be to explain away an observed association.
Intent-to-treat
Analyze units by their assigned condition, even if they did not comply. This preserves randomization.
MDP
Markov decision process: the standard model for sequential decisions with states, actions, transitions, rewards, and policies.
Posterior
The updated distribution of beliefs after combining prior information with observed data.
Propensity score
The probability of receiving treatment given observed covariates.
Randomization
Assigning treatment by a chance mechanism so treatment groups are comparable in expectation.
Reward
The feedback signal an RL agent tries to maximize over time.
Washout
A buffer period between conditions in a crossover experiment to reduce carryover effects.