Gill jeff bao (36 risultati)

Condizione: New.

Condizione: New.

paperback. Condizione: New. Brand new book, sourced directly from publisher. Dispatch time is 24-48 hours from our warehouse. Book will be sent in robust, secure packaging to ensure it reaches you securely.

Paperback. Condizione: New. This Element introduces the basics of Bayesian regression modeling using modern computational tools. This Element only assumes that the reader has taken a basic statistics course and has seen Bayesian inference at the introductory level of Gill and Bao (2024). Some matrix algebra knowledge is assumed but the authors walk carefully through the necessary structures at the start of this Element. At the end of the process readers will fully understand how Bayesian regression models are developed and estimated, including linear and nonlinear versions. The sections cover theoretical principles and real-world applications in order to provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in R and Python is provided throughout.…

Paperback. Condizione: New. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout.…

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: Brand New. 116 pages. 6.00x0.24x9.00 inches. In Stock.

Condizione: New.

Paperback. Condizione: Brand New. 116 pages. 6.00x0.24x9.00 inches. In Stock.

Condizione: New.

Paperback. Condizione: Brand New. 75 pages. 6.00x0.23x9.00 inches. In Stock.

Condizione: As New. Unread book in perfect condition.

Condizione: As New. Unread book in perfect condition.

hardcover. Condizione: Very Good.

Condizione: New.

Hardback. Condizione: New. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout.…

Condizione: As New. Unread book in perfect condition.

Hardback. Condizione: New. This Element introduces the basics of Bayesian regression modeling using modern computational tools. This Element only assumes that the reader has taken a basic statistics course and has seen Bayesian inference at the introductory level of Gill and Bao (2024). Some matrix algebra knowledge is assumed but the authors walk carefully through the necessary structures at the start of this Element. At the end of the process readers will fully understand how Bayesian regression models are developed and estimated, including linear and nonlinear versions. The sections cover theoretical principles and real-world applications in order to provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in R and Python is provided throughout.…

Condizione: New.

Condizione: New. In English.

Condizione: New.

Condizione: As New. Unread book in perfect condition.

Paperback. Condizione: New. This Element introduces the basics of Bayesian regression modeling using modern computational tools. This Element only assumes that the reader has taken a basic statistics course and has seen Bayesian inference at the introductory level of Gill and Bao (2024). Some matrix algebra knowledge is assumed but the authors walk carefully through the necessary structures at the start of this Element. At the end of the process readers will fully understand how Bayesian regression models are developed and estimated, including linear and nonlinear versions. The sections cover theoretical principles and real-world applications in order to provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in R and Python is provided throughout.…

Paperback. Condizione: New. In this Element, the authors introduce Bayesian probability and inference for social science students and practitioners starting from the absolute beginning and walk readers steadily through the Element. No previous knowledge is required other than that in a basic statistics course. At the end of the process, readers will understand the core tenets of Bayesian theory and practice in a way that enables them to specify, implement, and understand models using practical social science data. Chapters will cover theoretical principles and real-world applications that provide motivation and intuition. Because Bayesian methods are intricately tied to software, code in both R and Python is provided throughout.…

Condizione: New.

Condizione: New.

Hardcover. Condizione: Brand New. 116 pages. 6.00x0.31x9.00 inches. In Stock.

Condizione: New.

Hardcover. Condizione: Brand New. 75 pages. 6.00x0.31x9.00 inches. In Stock.