Editing Causal Inference (section)

== <span style="color: #FFFFFF;">Remembering</span> ==
* '''Causal Inference''' — The branch of statistics concerned with identifying cause-and-effect relationships.
* '''Counterfactual''' — The "What if?" scenario; what would have happened if a different action had been taken.
* '''Confounder''' — A variable that influences both the cause and the effect, creating a "spurious" correlation (e.g., 'Heat' causes both ice cream sales and shark attacks).
* '''Randomized Controlled Trial (RCT)''' — The "Gold Standard" of causal inference, where participants are randomly assigned to groups to eliminate confounders.
* '''Observational Study''' — A study where the researcher does not control the assignment of treatment (common in economics and sociology).
* '''Selection Bias''' — When the people who choose a treatment are different from those who don't (e.g., people who take vitamins are already more health-conscious).
* '''Instrumental Variable (IV)''' — A variable that affects the treatment but has no direct effect on the outcome, used to "isolate" a causal effect in observational data.
* '''Propensity Score Matching''' — A technique that attempts to estimate the effect of a treatment by accounting for the covariates that predict receiving the treatment.
* '''Directed Acyclic Graph (DAG)''' — A visual map of causal relationships (nodes and arrows).
* '''Do-calculus''' — A mathematical framework developed by Judea Pearl for intervening in a causal system.
* '''Average Treatment Effect (ATE)''' — The average difference in outcomes between the treated and untreated groups.
* '''Natural Experiment''' — An empirical study where individuals are exposed to the experimental and control conditions as determined by nature or other factors outside the control of the investigators (e.g., a change in law in one state but not another).
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