Month: October 2022

Causal effect refers to the relationship between two variables, where one variable (the cause) influences the other variable (the effect). The causal effect measures the impact of the cause on the effect, controlling for other possible factors that may influence

There are different types of causal effects, and the choice of which type to focus on may depend on the research question, study design, and available data. Some common types of causal effects include: Individual Treatment Effect (ITE): The effect

Causality is an essential concept in data science because it helps us understand the underlying mechanisms that drive relationships between variables, which is critical for making accurate predictions and designing effective interventions. In many data science applications, the goal is