The Data Analyst's Guide to Cause and Effect: An Introduction Causal Inference in Practice

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Bol The Data Analyst′s Guide to Cause and Effect offers a clear, practical roadmap built around the EEESI workflow—Estimand, Estimator, Estimate, Simulation-based Inference. This book provides a systematic approach to defining, estimating, and validating causal effects, allowing readers to learn to apply modern techniques and move beyond simple associations to make credible causal inferences that inform theory, policy, and practice.

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The Data Analyst′s Guide to Cause and Effect offers a clear, practical roadmap built around the EEESI workflow—Estimand, Estimator, Estimate, Simulation-based Inference. This book provides a systematic approach to defining, estimating, and validating causal effects, allowing readers to learn to apply modern techniques and move beyond simple associations to make credible causal inferences that inform theory, policy, and practice.


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Merk Sage Pubns
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  • 9798348848712
Maat


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