How do you differentiate between direct and indirect effects in causal analysis?

Direct effects refer to the immediate impact one variable has on another, without any intermediary steps. It's the effect that is not mediated by another variable in the model. On the other hand, indirect effects, also known as mediated effects, occur when the relationship between two variables is influenced by one or more intervening variables. These effects are crucial for understanding the underlying mechanisms and processes that drive observable outcomes.

Let's consider a practical example relevant to the role of a Data Scientist, which involves understanding user engagement on a tech platform. Imagine we're interested in evaluating the effect of a new feature release on user engagement, measured by daily active users (DAU). In this scenario, the direct effect would be...