causal inference and causal relationships
Causal inference refers to the process of determining cause and effect relationships between variables. It involves figuring out whether a particular condition or action directly leads to a specific outcome or if they are just coincidentally related. Causal relationships, on the other hand, describe the cause and effect connections between variables, showing how changes in one variable lead to changes in another.
Requires login.
Related Concepts (1)
Similar Concepts
- bayesian inference in causal models
- causal explanations
- causal graphs and networks
- causal inference
- causal inference methods
- causal inferences
- causal reasoning
- causal relationships
- causal relationships in social sciences
- causality
- cause and effect relationships
- coincidence vs causal relationship
- correlation and causation
- reasoning and inference
- the nature of causality