Causal Graph
A directed acyclic graph that mathematically visualizes the true cause-and-effect relationships between random variables in a complex data generating process.
Think of It Like This
Like drawing a flowchart that strictly points out that rain causes both umbrellas and wet grass, preventing you from thinking umbrellas cause wet grass.
By explicitly drawing nodes for features and directional arrows for causal links, researchers can identify confounding variables and biases that pure correlation models would blindly exploit. This structural framework is absolutely essential for calculating interventions, like predicting what would happen to patient recovery times if a new drug were forcefully administered.