causal inference
Causal inference is a process of determining the cause-and-effect relationship between two or more variables based on observational or experimental data. It aims to understand whether a certain factor influences an outcome by accounting for other potential causes and controlling for confounding factors.
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Related Concepts (12)
- bayesian causal reasoning
- causal pathways
- causal reasoning
- causal relationships
- causality
- correlation and causation
- correlation vs causation
- experimental variables and manipulation in aspect experiments
- longitudinal aspects in experimental research
- mediation and moderation in aspect experiments
- replication and generalizability in aspect experiments
- the role of control groups in aspect experiments
Similar Concepts
- bayesian inference
- bayesian inference in causal models
- causal attribution
- causal discovery
- causal explanations
- causal fallacies
- causal inference and causal relationships
- causal inference in aspect experiments
- causal inference methods
- causal inferences
- inference
- inferential reasoning
- reasoning and inference
- statistical inference
- type inference