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The Data Analyst’s Guide to Cause and Effect: An Introduction to Causal Inference in Practice (Quantitative Applications in the Social Sciences) - Tapa blanda
Sinopsis
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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Acerca de los autores
Theiss Bendixen is a PhD, quantitative consultant, and independent researcher. To date, he has written two popular science books, a co-edited
volume, as well as more than 40 academic works, including tutorials, quantitative empirical papers, and technical commentaries. He consults on statistical modelling in both industry, academia, and non-profits, applying causal inference techniques across scientific disciplines. He currently works in the pharmaceutical sector.
Personal website: www.theissbendixen.com
Benjamin Grant Purzycki is Associate Professor at Aarhus University. He is a cognitive and evolutionary cultural anthropologist and focuses on the causal role of various demographic and cultural factors on human cooperation. He has conducted fieldwork in the Tyva Republic (Russia) and managed large, cross-cultural projects. His most recent books include The Minds of Gods: New Horizons in the Naturalistic Study of Religion (Bloomsbury), Ethnographic Free-List Data (Sage), and Morality and the Gods (Cambridge University Press).
Personal website: www.bgpurzycki.wordpress.com
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The Data Analysts Guide to Cause and Effect (Paperback)
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Paperback. Condición: new. Paperback. The Data Analysts Guide to Cause and Effect offers a clear, practical roadmap built around the EEESI workflowEstimand, 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. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. Nº de ref. del artículo: 9798348848712
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The Data Analyst's Guide to Cause and Effect
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Paperback. Condición: New. 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. Nº de ref. del artículo: LU-9798348848712
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The Data Analyst's Guide to Cause and Effect: An Introduction to Causal Inference in Practice (Quantitative Applications in the Social Sciences)
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Taschenbuch. Condición: Neu. Neuware - 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. Nº de ref. del artículo: 9798348848712
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Paperback. Condición: new. Paperback. The Data Analysts Guide to Cause and Effect offers a clear, practical roadmap built around the EEESI workflowEstimand, 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. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability. Nº de ref. del artículo: 9798348848712
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Paperback. Condición: new. Paperback. The Data Analysts Guide to Cause and Effect offers a clear, practical roadmap built around the EEESI workflowEstimand, 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. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9798348848712
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The Data Analyst's Guide to Cause and Effect
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Paperback. Condición: New. 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. Nº de ref. del artículo: LU-9798348848712
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The Data Analyst's Guide to Cause and Effect
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Taschenbuch. Condición: Neu. Neuware -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. 168 pp. Englisch. Nº de ref. del artículo: 9798348848712
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