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A Practical Guide To Brain Data Analysis


A Practical Guide To Brain Data Analysis
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A Practical Guide To Brain Data Analysis


A Practical Guide To Brain Data Analysis
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Author : Joao Paulo Vieito
language : en
Publisher: World Scientific
Release Date : 2016-12-21

A Practical Guide To Brain Data Analysis written by Joao Paulo Vieito and has been published by World Scientific this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-12-21 with Medical categories.


This book was developed to help students and researchers in the fields of economics, finance, law and other social science areas to understand and apply neuroscience. With the use of neuroscience technologies, it is now possible to understand how people make decisions in practice, using friendly and ecological experimental setups. The first half of the book studies the decision-making process and explains how the brain is organized. It presents the brain as a distributed processing system, shows how to record brain activities, and how to combine neurosciences and statistical tools to design experiments. In the last chapters, experiments on stock market decision, dilemma judgment, vote decision and understanding of media propaganda are described and discussed.



A Practical Guide To Brain Data Analysis


A Practical Guide To Brain Data Analysis
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Author : Armando Freitas Rocha
language : en
Publisher:
Release Date : 2016

A Practical Guide To Brain Data Analysis written by Armando Freitas Rocha and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016 with Decision making categories.


"This book was developed to help students and researchers in the fields of economics, finance, law and other social science areas to understand and apply neuroscience. With the use of neuroscience technologies, it is now possible to understand how people make decisions in practice, using friendly and ecological experimental setups. The first half of the book studies the decision-making process and explains how the brain is organized. It presents the brain as a distributed processing system, shows how to record brain activities, and how to combine neurosciences and statistical tools to design experiments. In the last chapters, experiments on stock market decision, dilemma judgment, vote decision and understanding of media propaganda are described and discussed."--Publisher's website.



A Practical Guide To Data Analysis Using R


A Practical Guide To Data Analysis Using R
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Author : John H. Maindonald
language : en
Publisher: Cambridge University Press
Release Date : 2024-05-31

A Practical Guide To Data Analysis Using R written by John H. Maindonald 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 2024-05-31 with Computers categories.


Examples from diverse areas of statistical application demonstrate the use of R for data analysis and associated graphics.



Case Studies In Neural Data Analysis


Case Studies In Neural Data Analysis
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Author : Mark A. Kramer
language : en
Publisher: MIT Press
Release Date : 2016-11-04

Case Studies In Neural Data Analysis written by Mark A. Kramer and has been published by MIT Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-04 with Science categories.


A practical guide to neural data analysis techniques that presents sample datasets and hands-on methods for analyzing the data. As neural data becomes increasingly complex, neuroscientists now require skills in computer programming, statistics, and data analysis. This book teaches practical neural data analysis techniques by presenting example datasets and developing techniques and tools for analyzing them. Each chapter begins with a specific example of neural data, which motivates mathematical and statistical analysis methods that are then applied to the data. This practical, hands-on approach is unique among data analysis textbooks and guides, and equips the reader with the tools necessary for real-world neural data analysis. The book begins with an introduction to MATLAB, the most common programming platform in neuroscience, which is used in the book. (Readers familiar with MATLAB can skip this chapter and might decide to focus on data type or method type.) The book goes on to cover neural field data and spike train data, spectral analysis, generalized linear models, coherence, and cross-frequency coupling. Each chapter offers a stand-alone case study that can be used separately as part of a targeted investigation. The book includes some mathematical discussion but does not focus on mathematical or statistical theory, emphasizing the practical instead. References are included for readers who want to explore the theoretical more deeply. The data and accompanying MATLAB code are freely available on the authors' website. The book can be used for upper-level undergraduate or graduate courses or as a professional reference. A version of this textbook with all of the examples in Python is available on the MIT Press website.



Head First Data Analysis


Head First Data Analysis
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Author : Michael Milton
language : en
Publisher: "O'Reilly Media, Inc."
Release Date : 2009-07-24

Head First Data Analysis written by Michael Milton and has been published by "O'Reilly Media, Inc." this book supported file pdf, txt, epub, kindle and other format this book has been release on 2009-07-24 with Business & Economics categories.


A guide for data managers and analyzers. It shares guidelines for identifying patterns, predicting future outcomes, and presenting findings to others.



Making Sense Of Data I


Making Sense Of Data I
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Author : Glenn J. Myatt
language : en
Publisher: John Wiley & Sons
Release Date : 2014-07-02

Making Sense Of Data I written by Glenn J. Myatt 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 2014-07-02 with Mathematics categories.


Praise for the First Edition “...a well-written book on data analysis and data mining that provides an excellent foundation...” —CHOICE “This is a must-read book for learning practical statistics and data analysis...” —Computing Reviews.com A proven go-to guide for data analysis, Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition focuses on basic data analysis approaches that are necessary to make timely and accurate decisions in a diverse range of projects. Based on the authors’ practical experience in implementing data analysis and data mining, the new edition provides clear explanations that guide readers from almost every field of study. In order to facilitate the needed steps when handling a data analysis or data mining project, a step-by-step approach aids professionals in carefully analyzing data and implementing results, leading to the development of smarter business decisions. The tools to summarize and interpret data in order to master data analysis are integrated throughout, and the Second Edition also features: Updated exercises for both manual and computer-aided implementation with accompanying worked examples New appendices with coverage on the freely available TraceisTM software, including tutorials using data from a variety of disciplines such as the social sciences, engineering, and finance New topical coverage on multiple linear regression and logistic regression to provide a range of widely used and transparent approaches Additional real-world examples of data preparation to establish a practical background for making decisions from data Making Sense of Data I: A Practical Guide to Exploratory Data Analysis and Data Mining, Second Edition is an excellent reference for researchers and professionals who need to achieve effective decision making from data. The Second Edition is also an ideal textbook for undergraduate and graduate-level courses in data analysis and data mining and is appropriate for cross-disciplinary courses found within computer science and engineering departments.



Successful Qualitative Research


Successful Qualitative Research
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Author : Virginia Braun
language : en
Publisher: SAGE
Release Date : 2013-04-05

Successful Qualitative Research written by Virginia Braun and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-04-05 with Social Science categories.


This accessible, practical 'how to' guide provides students with a step-by-step toolkit of the why, when and how of qualitative methods, for anyone studying qualitative research or doing a research project.



Applied Longitudinal Data Analysis For Epidemiology


Applied Longitudinal Data Analysis For Epidemiology
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Author : Jos W. R. Twisk
language : en
Publisher: Cambridge University Press
Release Date : 2013-05-09

Applied Longitudinal Data Analysis For Epidemiology written by Jos W. R. Twisk 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 2013-05-09 with Medical categories.


A practical guide to the most important techniques available for longitudinal data analysis, essential for non-statisticians and researchers.



Handbook Of Neuroimaging Data Analysis


Handbook Of Neuroimaging Data Analysis
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Author : Hernando Ombao
language : en
Publisher: CRC Press
Release Date : 2016-11-18

Handbook Of Neuroimaging Data Analysis written by Hernando Ombao and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-18 with Mathematics categories.


This book explores various state-of-the-art aspects behind the statistical analysis of neuroimaging data. It examines the development of novel statistical approaches to model brain data. Designed for researchers in statistics, biostatistics, computer science, cognitive science, computer engineering, biomedical engineering, applied mathematics, physics, and radiology, the book can also be used as a textbook for graduate-level courses in statistics and biostatistics or as a self-study reference for Ph.D. students in statistics, biostatistics, psychology, neuroscience, and computer science.



Linear Mixed Models


Linear Mixed Models
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Author : Brady T. West
language : en
Publisher: CRC Press
Release Date : 2014-07-17

Linear Mixed Models written by Brady T. West and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-17 with Mathematics categories.


Highly recommended by JASA, Technometrics, and other journals, the first edition of this bestseller showed how to easily perform complex linear mixed model (LMM) analyses via a variety of software programs. Linear Mixed Models: A Practical Guide Using Statistical Software, Second Edition continues to lead readers step by step through the process of fitting LMMs. This second edition covers additional topics on the application of LMMs that are valuable for data analysts in all fields. It also updates the case studies using the latest versions of the software procedures and provides up-to-date information on the options and features of the software procedures available for fitting LMMs in SAS, SPSS, Stata, R/S-plus, and HLM. New to the Second Edition A new chapter on models with crossed random effects that uses a case study to illustrate software procedures capable of fitting these models Power analysis methods for longitudinal and clustered study designs, including software options for power analyses and suggested approaches to writing simulations Use of the lmer() function in the lme4 R package New sections on fitting LMMs to complex sample survey data and Bayesian approaches to making inferences based on LMMs Updated graphical procedures in the software packages Substantially revised index to enable more efficient reading and easier location of material on selected topics or software options More practical recommendations on using the software for analysis A new R package (WWGbook) that contains all of the data sets used in the examples Ideal for anyone who uses software for statistical modeling, this book eliminates the need to read multiple software-specific texts by covering the most popular software programs for fitting LMMs in one handy guide. The authors illustrate the models and methods through real-world examples that enable comparisons of model-fitting options and results across the software procedures.