Introduction To Bayesian Data Analysis For Cognitive Science
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Introduction To Bayesian Data Analysis For Cognitive Science
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Author : Bruno Nicenboim
language : en
Publisher: CRC Press
Release Date : 2025-08-21
Introduction To Bayesian Data Analysis For Cognitive Science written by Bruno Nicenboim and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-08-21 with Psychology categories.
This book introduces Bayesian data analysis and Bayesian cognitive modeling to students and researchers in cognitive science (e.g., linguistics, psycholinguistics, psychology, computer science), with a particular focus on modeling data from planned experiments. The book relies on the probabilistic programming language Stan and the R package brms, which is a front-end to Stan. The book only assumes that the reader is familiar with the statistical programming language R, and has basic high school exposure to pre-calculus mathematics; some of the important mathematical constructs needed for the book are introduced in the first chapter. Through this book, the reader will be able to develop a practical ability to apply Bayesian modeling within their own field. The book begins with an informal introduction to foundational topics such as probability theory, and univariate and bi-/multivariate discrete and continuous random variables. Then, the application of Bayes' rule for statistical inference is introduced with several simple analytical examples that require no computing software; the main insight here is that the posterior distribution of a parameter is a compromise between the prior and the likelihood functions. The book then gradually builds up the regression framework using the brms package in R, ultimately leading to hierarchical regression modeling (aka the linear mixed model). Along the way, there is detailed discussion about the topic of prior selection, and developing a well-defined workflow. Later chapters introduce the Stan programming language, and cover advanced topics using practical examples: contrast coding, model comparison using Bayes factors and cross-validation, hierarchical models and reparameterization, defining custom distributions, measurement error models and meta-analysis, and finally, some examples of cognitive models: multinomial processing trees, finite mixture models, and accumulator models. Additional chapters, appendices, and exercises are provided as online materials and can be accessed here: https://github.com/bnicenboim/bayescogsci.
The Routledge Handbook Of Experimental Linguistics
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Author : Sandrine Zufferey
language : en
Publisher: Taylor & Francis
Release Date : 2023-09-04
The Routledge Handbook Of Experimental Linguistics written by Sandrine Zufferey and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-09-04 with Language Arts & Disciplines categories.
The Routledge Handbook of Experimental Linguistics provides an up-to-date and accessible overview of various ways in which experiments are used across all domains of linguistics and surveys the range of state-of-the-art methods that can be applied to analyse the language of populations with a wide range of linguistic profiles. Each chapter provides a step-by-step introduction to theoretical and methodological challenges and critically presents a wide range of studies in various domains of experimental linguistics. This handbook: Provides a unified perspective on the data, methods and findings stemming from all experimental research in linguistics Covers many different subfields of linguistics, including argumentation theory, discourse studies and typology Provides an introduction to classical as well as new methods to conduct experiments such as eye tracking and brain imaging Features a range of internationally renowned academics Shows how experimental research can be used to study populations with various linguistic profiles, including young children, people with linguistic impairments, older adults, language learners and bilingual speakers Providing readers with a wealth of theoretical and practical information in order to guide them in designing methodologically sound linguistic experiments, this handbook is essential reading for scholars and students researching in all areas of linguistics.
Experimentology
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Author : Michael C. Frank
language : en
Publisher: MIT Press
Release Date : 2025-07-01
Experimentology written by Michael C. Frank and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Psychology categories.
An engaging research methods text integrating a classic approach to conducting experiments in psychology with open science practices and values. How does a researcher run a high-quality psychology experiment? What time-tested methods should be used, and how can more robust and accurate results be achieved? A dynamic collaboration between groundbreaking cognitive scientist Michael Frank and a diverse cohort of researchers innovating in the field—Mika Braginsky, Julie Cachia, Nicholas Coles, Tom Hardwicke, Robert Hawkins, Maya Mathur, and Rondeline Williams—Experimentology introduces the art of the modern psychological experiment with an emphasis on open science values of accessibility and transparency. Experimentology follows the timeline of an experiment, with sections covering basic foundations, planning, execution, data-gathering and analysis, and reporting. Narrative examples from a range of subdisciplines, including cognitive, developmental, and social psychology, model each component and account for the pitfalls that can undermine the reliability, validity, and replicability of results. Through an embrace of open science strategies such as data sharing and preregistration, Experimentology shows how the challenges of the replication crisis can be met constructively and collaboratively. Written for a global audience, Experimentology updates a classic research methods textbook with a new focus on ethics and the benefits of open science.
Doing Bayesian Data Analysis
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Author : John Kruschke
language : en
Publisher: Academic Press
Release Date : 2010-11-25
Doing Bayesian Data Analysis written by John Kruschke and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-25 with Mathematics categories.
There is an explosion of interest in Bayesian statistics, primarily because recently created computational methods have finally made Bayesian analysis tractable and accessible to a wide audience. Doing Bayesian Data Analysis, A Tutorial Introduction with R and BUGS, is for first year graduate students or advanced undergraduates and provides an accessible approach, as all mathematics is explained intuitively and with concrete examples. It assumes only algebra and 'rusty' calculus. Unlike other textbooks, this book begins with the basics, including essential concepts of probability and random sampling. The book gradually climbs all the way to advanced hierarchical modeling methods for realistic data. The text provides complete examples with the R programming language and BUGS software (both freeware), and begins with basic programming examples, working up gradually to complete programs for complex analyses and presentation graphics. These templates can be easily adapted for a large variety of students and their own research needs.The textbook bridges the students from their undergraduate training into modern Bayesian methods. - Accessible, including the basics of essential concepts of probability and random sampling - Examples with R programming language and BUGS software - Comprehensive coverage of all scenarios addressed by non-bayesian textbooks- t-tests, analysis of variance (ANOVA) and comparisons in ANOVA, multiple regression, and chi-square (contingency table analysis). - Coverage of experiment planning - R and BUGS computer programming code on website - Exercises have explicit purposes and guidelines for accomplishment
Sentence Comprehension As A Cognitive Process
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Author : Shravan Vasishth
language : en
Publisher: Cambridge University Press
Release Date : 2021-11-11
Sentence Comprehension As A Cognitive Process written by Shravan Vasishth and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-11-11 with Computers categories.
Presents a computational model of sentence processing that is grounded in decades of research in cognitive psychology and AI.
An Introduction To Model Based Cognitive Neuroscience
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Author : Birte U. Forstmann
language : en
Publisher: Springer
Release Date : 2015-04-20
An Introduction To Model Based Cognitive Neuroscience written by Birte U. Forstmann and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-04-20 with Medical categories.
Two recent innovations, the emergence of formal cognitive models and the addition of cognitive neuroscience data to the traditional behavioral data, have resulted in the birth of a new, interdisciplinary field of study: model-based cognitive neuroscience. Despite the increasing scientific interest in model-based cognitive neuroscience, few active researchers and even fewer students have a good knowledge of the two constituent disciplines. The main goal of this edited collection is to promote the integration of cognitive modeling and cognitive neuroscience. Experts in the field will provide tutorial-style chapters that explain particular techniques and highlight their usefulness through concrete examples and numerous case studies. The book will also include a thorough list of references pointing the reader towards additional literature and online resources.
Stevens Handbook Of Experimental Psychology And Cognitive Neuroscience Methodology
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Author :
language : en
Publisher: John Wiley & Sons
Release Date : 2018-02-12
Stevens Handbook Of Experimental Psychology And Cognitive Neuroscience Methodology written by and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2018-02-12 with Psychology categories.
V. Methodology: E. J. Wagenmakers (Volume Editor) Topics covered include methods and models in categorization; cultural consensus theory; network models for clinical psychology; response time modeling; analyzing neural time series data; models and methods for reinforcement learning; convergent methods of memory research; theories for discriminating signal from noise; bayesian cognitive modeling; mathematical modeling in cognition and cognitive neuroscience; the stop-signal paradigm; hypothesis testing and statistical inference; model comparison in psychology; fmri; neural recordings; open science; neural networks and neurocomputational modeling; serial versus parallel processing; methods in psychophysics.
Visualization For Social Data Science
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Author : Roger Beecham
language : en
Publisher: CRC Press
Release Date : 2025-09-05
Visualization For Social Data Science written by Roger Beecham and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-09-05 with Mathematics categories.
"This is an important book on an important topic. I particularly like the examples showing different visualizations of the same data and the parallel presentation of graphics and code. And I absolutely love the chapter on visual storytelling. I can't wait to use this book in my classes."- Andrew Gelman, Department of Statistics and Department of Political Science, Columbia University, New York "A book that gives learners the inspiration, knowledge and worked examples to create cutting edge visualisations of their own."- James Chesire, Professor of Geographic Information and Cartography, University College London Visualization for Social Data Science provides end-to-end skills in visual data analysis. The book demonstrates how data graphics and modern statistics can be used in tandem to process, explore, model and communicate data-driven social science. It is packed with detailed data analysis examples, pushing you to do visual data analysis. As well as introducing, and demonstrating with code, a wide range of data visualizations for exploring patterns in data, Visualization for Social Data Science shows how models can be integrated with graphics to emphasise important structure and de-emphasise spurious structure and the role of data graphics in scientific communication -- in building trust and integrity. Many of the book’s influences are from data journalism, as well as information visualization and cartography. Each chapter introduces statistical and graphical ideas for analysis, underpinned by real social science datasets. Those ideas are then implemented via principled, step-by-step, workflows in the programming environment R. Key features include: • Extensive real-world data sets and data analysis scenarios in Geography, Public Health, Transportation, Political Science; • Code examples fully-integrated into main text, with code that builds in complexity and sophistication; • Quarto template files for each chapter to support literate programming practices; • Functional programming examples, using tidyverse, for generating empirical statistics (bootstrap resamples, permutation tests) and working programmatically over model outputs; • Unusual but important programming tricks for generating sophisticated data graphics such as network visualizations, dot-density maps, OD maps, glyphmaps, icon arrays, hypothetical outcome plots and graphical line-ups plots. Every data graphic in the book is implemented via ggplot2. • Chapters on uncertainty visualization and data storytelling that are uniquely accompanied with detailed, worked examples.
Regression Modeling For Linguistic Data
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Author : Morgan Sonderegger
language : en
Publisher: MIT Press
Release Date : 2023-06-06
Regression Modeling For Linguistic Data written by Morgan Sonderegger and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-06 with Science categories.
The first comprehensive textbook on regression modeling for linguistic data offers an incisive conceptual overview along with worked examples that teach practical skills for realistic data analysis. In the first comprehensive textbook on regression modeling for linguistic data in a frequentist framework, Morgan Sonderegger provides graduate students and researchers with an incisive conceptual overview along with worked examples that teach practical skills for realistic data analysis. The book features extensive treatment of mixed-effects regression models, the most widely used statistical method for analyzing linguistic data. Sonderegger begins with preliminaries to regression modeling: assumptions, inferential statistics, hypothesis testing, power, and other errors. He then covers regression models for non-clustered data: linear regression, model selection and validation, logistic regression, and applied topics such as contrast coding and nonlinear effects. The last three chapters discuss regression models for clustered data: linear and logistic mixed-effects models as well as model predictions, convergence, and model selection. The book’s focused scope and practical emphasis will equip readers to implement these methods and understand how they are used in current work. The only advanced discussion of modeling for linguists Uses R throughout, in practical examples using real datasets Extensive treatment of mixed-effects regression models Contains detailed, clear guidance on reporting models Equal emphasis on observational data and data from controlled experiments Suitable for graduate students and researchers with computational interests across linguistics and cognitive science
Bayesian Cognitive Modeling
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Author : Michael D. Lee
language : en
Publisher: Cambridge University Press
Release Date : 2014-04-03
Bayesian Cognitive Modeling written by Michael D. Lee and has been published by Cambridge University Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-04-03 with Psychology categories.
Bayesian inference has become a standard method of analysis in many fields of science. Students and researchers in experimental psychology and cognitive science, however, have failed to take full advantage of the new and exciting possibilities that the Bayesian approach affords. Ideal for teaching and self study, this book demonstrates how to do Bayesian modeling. Short, to-the-point chapters offer examples, exercises, and computer code (using WinBUGS or JAGS, and supported by Matlab and R), with additional support available online. No advance knowledge of statistics is required and, from the very start, readers are encouraged to apply and adjust Bayesian analyses by themselves. The book contains a series of chapters on parameter estimation and model selection, followed by detailed case studies from cognitive science. After working through this book, readers should be able to build their own Bayesian models, apply the models to their own data, and draw their own conclusions.