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Active Statistics: Stories, Games, Problems, and Hands-on Demonstrations for Applied Regression and Causal Inference, Aki Vehtari, Andrew Gelman


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Цена: 3166.00р.
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Автор: Aki Vehtari, Andrew Gelman
Название:  Active Statistics: Stories, Games, Problems, and Hands-on Demonstrations for Applied Regression and Causal Inference
ISBN: 9781009436212
Издательство: Cambridge Academ
Классификация:

ISBN-10: 100943621X
Обложка/Формат: Paperback
Страницы: 368
Вес: 0.69 кг.
Дата издания: 31.03.2024
Язык: English
Иллюстрации: Worked examples or exercises
Размер: 177 x 255 x 23
Ключевые слова: MATHEMATICS / Probability & Statistics / General
Подзаголовок: Stories, games, problems, and hands-on demonstrations for applied regression and causal inference
Ссылка на Издательство: Link
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Поставляется из: Англии
Описание: This book provides statistics instructors and students with complete classroom material for a one- or two-semester course on applied regression and causal inference. It is built around 52 stories, 52 class-participation activities, 52 hands-on computer demonstrations, and 52 discussion problems that allow instructors and students to explore in a fun way the real-world complexity of the subject. The book fosters an engaging flipped classroom environment with a focus on visualization and understanding. The book provides instructors with frameworks for self-study or for structuring the course, along with tips for maintaining student engagement at all levels, and practice exam questions to help guide learning. Designed to accompany the authors previous textbook Regression and Other Stories, its modular nature and wealth of material allow this book to be adapted to different courses and texts or be used by learners as a hands-on workbook.


Causal Inference for Statistics, Social, and Biomedical Sciences

Автор: Imbens
Название: Causal Inference for Statistics, Social, and Biomedical Sciences
ISBN: 0521885884 ISBN-13(EAN): 9780521885881
Издательство: Cambridge Academ
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Цена: 8237.00 р.
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Описание: This text presents statistical methods for studying causal effects and discusses how readers can assess such effects in simple randomized experiments.

Counterfactuals and Causal Inference

Автор: Morgan
Название: Counterfactuals and Causal Inference
ISBN: 1107694167 ISBN-13(EAN): 9781107694163
Издательство: Cambridge Academ
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Цена: 5702.00 р.
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Описание: Cause-and-effect questions are the motivation for most research in the social, demographic, and health sciences. The counterfactual approach to causal analysis represents a unified framework for the prosecution of these questions. This second edition aims to convince more social scientists to take this approach when analyzing these core empirical questions.

Advanced Statistics for Testing Assumed Causal Relationships

Автор: Hooshang Nayebi
Название: Advanced Statistics for Testing Assumed Causal Relationships
ISBN: 3030547531 ISBN-13(EAN): 9783030547530
Издательство: Springer
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Цена: 11179.00 р.
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Описание: It presents that potential effects of each independent variable on the dependent variable are not limited to direct and indirect effects. The path analysis shows each independent variable has a pure effect on the dependent variable. So, it can be shown the unique contribution of each independent variable to the variation of the dependent variable.

Causality Tests In Econometrics: Choice of Causal Variables

Автор: B. Sreenivasulu et al.
Название: Causality Tests In Econometrics: Choice of Causal Variables
ISBN: 3659504041 ISBN-13(EAN): 9783659504044
Издательство: LAP LAMBERT Academic Publishing
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Цена: 7472.00 р.
Наличие на складе: Нет в наличии.

Описание: In the Present Book Chapter-I is an introductory one.Chapter-II describes the concept and causal relations by econometric models. It presents the different representations such as autoregressive, Moving – average and univariate representation of causality. Chapter-III explore lucidly the various tests for causality, we come across in econometrics. In regression analysis, researchers are interested in testing for the exogenity of variables this testing is closely related to the causality test proposed by Granger, which is explained in detail in this chapter. Chapter-IV gives the conclusions about the present study.The various relevant research articles have been presented under the title BIBLIOGRAPHY.

Mendelian Randomization: Methods for Causal Inference Using Genetic Variants

Автор: Burgess Stephen, Thompson Simon G.
Название: Mendelian Randomization: Methods for Causal Inference Using Genetic Variants
ISBN: 0367341840 ISBN-13(EAN): 9780367341848
Издательство: Taylor&Francis
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Цена: 27562.00 р.
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Описание: Mendelian randomization (MR) uses genetic instrumental variables to make inferences about causal effects based on observational data. It, therefore, can be a reliable way of assessing the causal nature of risk factors, such as biomarkers, for a wide range of disease outcomes.

Bayesian nonparametrics for causal inference and missing data

Автор: Daniels, Michael J.
Название: Bayesian nonparametrics for causal inference and missing data
ISBN: 036734100X ISBN-13(EAN): 9780367341008
Издательство: Taylor&Francis
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Цена: 15004.00 р.
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Sage handbook of regression analysis and causal inference

Название: Sage handbook of regression analysis and causal inference
ISBN: 1446252442 ISBN-13(EAN): 9781446252444
Издательство: Sage Publications
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Цена: 21384.00 р.
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A First Course in Causal Inference

Автор: Ding, Peng
Название: A First Course in Causal Inference
ISBN: 1032758627 ISBN-13(EAN): 9781032758626
Издательство: Taylor&Francis
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Цена: 9951.00 р.
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Causal Inference in Pharmaceutical Statistics

Автор: Fang, Yixin
Название: Causal Inference in Pharmaceutical Statistics
ISBN: 1032560142 ISBN-13(EAN): 9781032560144
Издательство: Taylor&Francis
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Цена: 15004.00 р.
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Causality and Causal Modelling in the Social Sciences

Автор: Federica Russo
Название: Causality and Causal Modelling in the Social Sciences
ISBN: 9048179963 ISBN-13(EAN): 9789048179961
Издательство: Springer
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Цена: 20962.00 р.
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Описание: This investigation into causal modelling presents the rationale of causality; i.e. what guides reasoning in causal modeling. In contrast to the dominant paradigm, it argues that causal models are governed by a variation, rather than regularity or invariance.

Statistical Methods for Dynamic Treatment Regimes

Название: Statistical Methods for Dynamic Treatment Regimes
ISBN: 1461474272 ISBN-13(EAN): 9781461474272
Издательство: Springer
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Цена: 11179.00 р.
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Описание: Statistical Methods for Dynamic Treatment Regimes shares state of the art of statistical methods developed to address questions of estimation and inference for dynamic treatment regimes, a branch of personalized medicine.

Causality In Crisis?: Statistical Methods & Search for Causal Knowledge in Social Sciences

Автор: Stephen Turner, Vaughn McKim
Название: Causality In Crisis?: Statistical Methods & Search for Causal Knowledge in Social Sciences
ISBN: 0268008248 ISBN-13(EAN): 9780268008246
Издательство: Wiley EDC
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Цена: 3259.00 р.
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Описание:

In the past fifty years statisticians and methodologists in the social sciences have developed and refined a family of closely related statistical methods for the study of social phenomena. While the value of such methods of analysis is universally acknowledged, their use has never been wholly uncontroversial. In 1993 prominent scholars from a variety of disciplines (social sciences, statistics, philosophy of science) gathered at the University of Notre Dame to debate whether causal modeling techniques old or new can really justify the drawing of causal conclusions on the basis of correlational statistical data. The resulting volume from that groundbreaking conference is Causality in Crisis? a comprehensive and sophisticated introduction to perhaps the most important set of issues confronting social scientific researchers in the 1990s and beyond.

In the essays presented here contributors critically reassess the widely accepted view that statistical methods of analysis can and do yield causal understanding of social phenomena. Although a number of technical issues receive attention, the overall emphasis is on the larger historical, philosophical, and conceptual perspectives that underlie and inform current methodological controversies.

The debates in Causality in Crisis? have far-ranging implications, for on their resolution hinges the question of what sort of knowledge of social life it is possible to achieve on the basis of non-experimental social scientific research. Any scholar who makes use of causal methods, as well as all who are affected by decisions reached on the basis of such methods, will have a stake in the challenging arguments put forth in this volume.


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