Tag: Experimental Design
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Causal Inference
Causal inference provides a framework for deducing the relationship between cause and effect using empirical data. It employs a variety of rigorous methods to ensure the validity of its findings, making it indispensable in fields such as policy evaluation, economics, and healthcare.
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Sensitivity Analysis
Sensitivity Analysis quantifies the impact of variable changes on a specific outcome within a model. Employed across various disciplines, it aids in risk assessment, model validation, and decision-making, offering metrics to represent sensitivity.
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Null Hypothesis
In statistical hypothesis testing, the null hypothesis asserts a lack of effect and serves as a baseline for evaluation. Specific tests are employed to assess evidence, leading to either the rejection or the failure to reject this initial assumption. This methodology is pivotal in both scientific inquiry and rational decision-making.