Dasgupta tirthankar (20 resultados)

Idioma: Inglés
Editorial: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
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Editorial: Chapman and Hall/CRC, 2026
Serie: Libro 120 de 126 - Chapman & Hall/CRC Texts in Statistical Science
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Taschenbuch. Condición: Neu. Indian Sign Language Machine Translation and Lexical Data Acquisition | Tirthankar Dasgupta (u. a.) | Taschenbuch | Englisch | LAP Lambert Academic Publishing | EAN 9783659349065 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.…

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Editorial: Chapman and Hall/CRC, 2026
Serie: Libro 120 de 126 - Chapman & Hall/CRC Texts in Statistical Science
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Idioma: Inglés
Editorial: Chapman and Hall/CRC, 2026
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Idioma: Inglés
Editorial: Taylor & Francis Ltd, 2026
Serie: Libro 120 de 126 - Chapman & Hall/CRC Texts in Statistical Science
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Idioma: Inglés
Editorial: Chapman and Hall/CRC, 2026
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Idioma: Inglés
Editorial: Taylor and Francis Ltd, GB, 2026
Serie: Libro 120 de 126 - Chapman & Hall/CRC Texts in Statistical Science
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Librería: Rarewaves.com USA, London, LONDO, Reino UnidoRarewaves.com USA
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Hardback. Condición: New. Design of experiments is, in essence, a disciplined way to learn about cause and effect. Modern experiments can involve a few to millions of units and hundreds or thousands of covariates. These settings demand tools that are flexible, transparent, and faithful to the underlying design in order to reach reliable conclusions about which interventions work and which ones do not. This book provides a modern, accessible, and computationally supported introduction to experimental design grounded firmly in randomization and the formulation of ideas and methods in terms of potential outcomes. Instead of prescribing a model for each design, we begin with the treatment assignment mechanism and link it directly to the observed outcomes through the potential outcomes framework. This formulation illuminates how changing the design changes the analysis, and it naturally distinguishes finite-population inference from super-population modeling. The book also incorporates new developments at the interface of causal inference and experimental design, many stemming from the authors' recent collaborative research efforts.Strengthens the link between design and analysis, enabling students to see immediately how the structure of an experiment shapes the exact tools used to analyze it.Teaches foundational concepts without assuming linear-model assumptions.Equips readers with the tools needed to analyze non-standard and complex experiments, whose randomization mechanisms fall outside the scope of traditional textbooks.Support students with limited programming experience by providing algorithms and code throughout the book, enabling them to implement randomization-based methods easily and efficiently.This book is a textbook for one/two semester course on introductory experimental design.…

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Idioma: Inglés
Editorial: Taylor and Francis Ltd, GB, 2026
Serie: Libro 120 de 126 - Chapman & Hall/CRC Texts in Statistical Science
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Hardback. Condición: New. Design of experiments is, in essence, a disciplined way to learn about cause and effect. Modern experiments can involve a few to millions of units and hundreds or thousands of covariates. These settings demand tools that are flexible, transparent, and faithful to the underlying design in order to reach reliable conclusions about which interventions work and which ones do not. This book provides a modern, accessible, and computationally supported introduction to experimental design grounded firmly in randomization and the formulation of ideas and methods in terms of potential outcomes. Instead of prescribing a model for each design, we begin with the treatment assignment mechanism and link it directly to the observed outcomes through the potential outcomes framework. This formulation illuminates how changing the design changes the analysis, and it naturally distinguishes finite-population inference from super-population modeling. The book also incorporates new developments at the interface of causal inference and experimental design, many stemming from the authors' recent collaborative research efforts.Strengthens the link between design and analysis, enabling students to see immediately how the structure of an experiment shapes the exact tools used to analyze it.Teaches foundational concepts without assuming linear-model assumptions.Equips readers with the tools needed to analyze non-standard and complex experiments, whose randomization mechanisms fall outside the scope of traditional textbooks.Support students with limited programming experience by providing algorithms and code throughout the book, enabling them to implement randomization-based methods easily and efficiently.This book is a textbook for one/two semester course on introductory experimental design.…

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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Autor/Autorin: Dasgupta TirthankarSenior Research Scholar and PhD Student from the Department of Computer Science and Engineering, Indian Institute of Technology Kharagpur.www.cse.iitkgp.ac.in/~tdgThis book presents a structure transfer framewo.…

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Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - This book presents a structure transfer framework for the English-To-ISL machine translation system and a dictionary framework that is used to associate signs cor- responding to a given English, Hindi or Bengali text. The book further discusses how to use this dictionary framework to annotate the complex phonological information of a sign language using the Hamburg Sign Language Notation System (HamNoSys).…

Idioma: Inglés
Editorial: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
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Librería: Majestic Books, Hounslow, Reino UnidoMajestic Books
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Condición: New. Print on Demand pp. 140 2:B&W 6 x 9 in or 229 x 152 mm Perfect Bound on Creme w/Gloss Lam.

Idioma: Inglés
Editorial: VDM Verlag Dr. Mueller Aktiengesellschaft & Co. KG, 2013
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Condición: New. PRINT ON DEMAND pp. 140.

Idioma: Inglés
Editorial: CRC Press, 2026
Serie: Libro 120 de 126 - Chapman & Hall/CRC Texts in Statistical Science
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Idioma: Inglés
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Hardcover. Condición: new. Hardcover. Design of experiments is, in essence, a disciplined way to learn about cause and effect. Modern experiments can involve a few to millions of units and hundreds or thousands of covariates. These settings demand tools that are flexible, transparent, and faithful to the underlying design in order to reach reliable conclusions about which interventions work and which ones do not. This book provides a modern, accessible, and computationally supported introduction to experimental design grounded firmly in randomization and the formulation of ideas and methods in terms of potential outcomes. Instead of prescribing a model for each design, we begin with the treatment assignment mechanism and link it directly to the observed outcomes through the potential outcomes framework. This formulation illuminates how changing the design changes the analysis, and it naturally distinguishes finite-population inference from super-population modeling. The book also incorporates new developments at the interface of causal inference and experimental design, many stemming from the authors recent collaborative research efforts.Strengthens the link between design and analysis, enabling students to see immediately how the structure of an experiment shapes the exact tools used to analyze it.Teaches foundational concepts without assuming linear-model assumptions.Equips readers with the tools needed to analyze non-standard and complex experiments, whose randomization mechanisms fall outside the scope of traditional textbooks.Support students with limited programming experience by providing algorithms and code throughout the book, enabling them to implement randomization-based methods easily and efficiently.This book is a textbook for one/two semester course on introductory experimental design. This book provides a modern, accessible, and computationally supported introduction to experimental design grounded firmly in randomization and the formulation of ideas and methods in terms of potential outcomes. The book also incorporates new developments at the interface of causal inference and experimental design. 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.…

Idioma: Inglés
Editorial: CRC Press, 2026
Serie: Libro 120 de 126 - Chapman & Hall/CRC Texts in Statistical Science
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Librería: moluna, Greven, Alemaniamoluna
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Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Tirthankar Dasgupta is a Professor of Statistics at Rutgers University, New Jersey. Prior to joining Rutgers University, he served as a faculty member at Harvard University. His primary research interests include experimental design and causal inf.…

Idioma: Inglés
Editorial: Chapman And Hall/CRC, 2026
Serie: Libro 120 de 126 - Chapman & Hall/CRC Texts in Statistical Science
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Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH
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Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Design of experiments is, in essence, a disciplined way to learn about cause and effect. Modern experiments can involve a few to millions of units and hundreds or thousands of covariates. These settings demand tools that are flexible, transparent, and faithful to the underlying design in order to reach reliable conclusions about which interventions work and which ones do not. This book provides a modern, accessible, and computationally supported introduction to experimental design grounded firmly in randomization and the formulation of ideas and methods in terms of potential outcomes. Instead of prescribing a model for each design, we begin with the treatment assignment mechanism and link it directly to the observed outcomes through the potential outcomes framework. This formulation illuminates how changing the design changes the analysis, and it naturally distinguishes finite-population inference from super-population modeling. The book also incorporates new developments at the interface of causal inference and experimental design, many stemming from the authors' recent collaborative research efforts. - Strengthens the link between design and analysis, enabling students to see immediately how the structure of an experiment shapes the exact tools used to analyze it. - Teaches foundational concepts without assuming linear-model assumptions. - Equips readers with the tools needed to analyze non-standard and complex experiments, whose randomization mechanisms fall outside the scope of traditional textbooks. - Support students with limited programming experience by providing algorithms and code throughout the book, enabling them to implement randomization-based methods easily and efficiently. This book is a textbook for one/two semester course on introductory experimental design.…
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Editorial: Chapman and Hall/CRC, 2026
Serie: Libro 120 de 126 - Chapman & Hall/CRC Texts in Statistical Science
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Librería: preigu, Osnabrück, Alemaniapreigu
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Buch. Condición: Neu. Introduction to Modern Randomization-Based Design and Analysis for Causal Inference | Tirthankar Dasgupta (u. a.) | Buch | Einband - fest (Hardcover) | Englisch | 2026 | Chapman and Hall/CRC | EAN 9780367500986 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …