Bayesian Data Analysis for the Behavioral and Neural Sciences (Hardcover)

Todd E. Hudson

ISBN 10: 1108835562 / ISBN 13: 9781108835565

Published by Cambridge University Press, Cambridge, 2021

About this Item

Hardcover. This textbook bypasses the need for advanced mathematics by providing in-text computer code, allowing students to explore Bayesian data analysis without the calculus background normally considered a prerequisite for this material. Now, students can use the best methods without needing advanced mathematical techniques. This approach goes beyond frequentist concepts of p-values and null hypothesis testing, using the full power of modern probability theory to solve real-world problems. The book offers a fully self-contained course, which demonstrates analysis techniques throughout with worked examples crafted specifically for students in the behavioral and neural sciences. The book presents two general algorithms that help students solve the measurement and model selection (also called hypothesis testing) problems most frequently encountered in real-world applications. This textbook teaches undergraduates in psychology, neuroscience, and medicine modern data analysis techniques. It uses non-calculus-based mathematics with examples specific to behavioral and neural sciences. Perfect for statistics courses, it shows students how to write code for their own data analyses, even those involving individual differences. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.

Seller Inventory # 9781108835565

Bibliographic Details

• Title: Bayesian Data Analysis for the Behavioral and Neural Sciences (Hardcover)
• Publisher: Cambridge University Press, Cambridge
• Publication Date: 2021
• Language: English
• ISBN 10: 1108835562
• ISBN 13: 9781108835565
• Binding: Hardcover
• Condition: new

About this title

Synopsis

This textbook bypasses the need for advanced mathematics by providing in-text computer code, allowing students to explore Bayesian data analysis without the calculus background normally considered a prerequisite for this material. Now, students can use the best methods without needing advanced mathematical techniques. This approach goes beyond “frequentist” concepts of p-values and null hypothesis testing, using the full power of modern probability theory to solve real-world problems. The book offers a fully self-contained course, which demonstrates analysis techniques throughout with worked examples crafted specifically for students in the behavioral and neural sciences. The book presents two general algorithms that help students solve the measurement and model selection (also called “hypothesis testing”) problems most frequently encountered in real-world applications.

About the Author

Todd E. Hudson is a professor of rehabilitation medicine at New York University's Grossman School of Medicine, holding cross-appointments in neurology, and also in the Department of Biomedical Engineering at the New York University Tandon School of Engineering. Dr Hudson has taught statistics, perception and sensory processes, experimental design, and/or advanced topics in neurobiology and behavior at several major universities, including Brandeis University and Columbia University. He co-founded, and serves as Chief Scientific Advisor to, Tactile Navigation Tools, LLC, which develops navigation aids for the visually impaired.