Interventions
In Data Science, interventions refer to the actions taken to modify a system or process in order to achieve a desired outcome. These interventions can be either experimental or observational, and are often used in fields such as healthcare, economics, and social sciences. In experimental interventions, researchers manipulate one or more variables in order to observe the effect on the outcome of interest. Observational interventions, on the other hand, involve identifying natural variations in the system and using statistical methods to estimate the causal effect of the intervention. Interventions can be used to test hypotheses, evaluate the effectiveness of policies or programs, and inform decision-making processes.
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