Some causal inference techniques

Causal inference techniques help determine if one thing actually causes another. For example, randomized controlled trials randomly assign people to different groups to see if a treatment works, reducing bias. Observational methods, like matching or regression, compare similar groups to isolate the effect of a variable, accounting for other factors. Instrumental variables use external factors linked to the cause to infer effects. Difference-in-differences compare changes over time between groups, helping identify causal effects when real experiments aren’t possible. These tools help researchers understand what truly influences outcomes, not just correlations.