Multivariate Statistical Analysis In Neuroscience


Multivariate Statistical Analysis In Neuroscience
DOWNLOAD

Download Multivariate Statistical Analysis In Neuroscience PDF/ePub or read online books in Mobi eBooks. Click Download or Read Online button to get Multivariate Statistical Analysis In Neuroscience book now. This website allows unlimited access to, at the time of writing, more than 1.5 million titles, including hundreds of thousands of titles in various foreign languages. If the content not found or just blank you must refresh this page





Multivariate Statistical Analysis In Neuroscience


Multivariate Statistical Analysis In Neuroscience
DOWNLOAD

Author : Giovanni Cugliari
language : en
Publisher: GRIN Verlag
Release Date : 2015-06-08

Multivariate Statistical Analysis In Neuroscience written by Giovanni Cugliari and has been published by GRIN Verlag this book supported file pdf, txt, epub, kindle and other format this book has been release on 2015-06-08 with Medical categories.


Research Paper (postgraduate) from the year 2015 in the subject Medicine - Other, grade: II Level Master, University of Pavia (Unit of Medical and Genomic Statistics), course: Medical and Genomic Statistics, language: English, abstract: Electroencephalography, commonly called 'EEG', estimates through the application of electrodes, the electrical activity of the brain (which is the sum of the electrical activity of each neuron). In recent years, with the goal of making more reliable the EEG, many researchers have turned their interest in the development of tools, methods and software. This thesis describes some best procedures for the experimental design, data visualization and descriptive or inferential statistical analysis. The application of statistical models to single or multiple subjects study-design are also described, including parametric and non-parametric approaches. Methods for processing multivariate data (PCA, ICA, clustering) were described. Re-sampling methods (bootstrap) using many randomly software-generated samples were also described. The aim of this work is to provide, with statistical concepts and examples, information on the qualitative and quantitative approaches related to the electroencephalographic signals. The work consists into three parts: INTRODUTION TO ELECTROENCEPHALOGRAPHY (GENERAL CHARACTERISTICS); DATA MINING AND STATISTICAL ANALYSIS; EXPERIMENTAL STUDY DESIGNS. The six works included in the section called “EXPERIMENTAL STUDY DESIGNS” analyze EEG alterations in the protocols: Electrocortical activity in dancers and non-dancers listening to different music genre and during imaginative dance motor activity; Electrocortical activity during monosynaptic reflex in athletes; Monitoring of electrocortical activity for evaluation of seasickness; Electrocortical activity in different body positions; Electrocortical activity in athletes and non-athletes during body balance tasks; Electrocortical responses in volunteers with and without specific experience watching movies including the execution of complex motor gestures. In the section called “OTHER INTERESTING THINGS” were included one work that analyze EMG (electromyography) alterations in pathological and healthy subjects in the protocol: Comparison between clinical diagnostic criteria of sleep bruxism and those provided by a validated portable holter. The described procedures can be used for clinical trials, although the studies proposed in this work do not refer to samples from pathological subjects. With its multi-specialist approach, through many theoretical and practical feedback, this work will be useful for specializing in neuroscience, statistics, engineering or physiology.



Multivariate Analysis For Neuroimaging Data


Multivariate Analysis For Neuroimaging Data
DOWNLOAD

Author : Atsushi Kawaguchi
language : en
Publisher: CRC Press
Release Date : 2021-07-01

Multivariate Analysis For Neuroimaging Data written by Atsushi Kawaguchi and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-07-01 with Mathematics categories.


This book describes methods for statistical brain imaging data analysis from both the perspective of methodology and from the standpoint of application for software implementation in neuroscience research. These include those both commonly used (traditional established) and state of the art methods. The former is easier to do due to the availability of appropriate software. To understand the methods it is necessary to have some mathematical knowledge which is explained in the book with the help of figures and descriptions of the theory behind the software. In addition, the book includes numerical examples to guide readers on the working of existing popular software. The use of mathematics is reduced and simplified for non-experts using established methods, which also helps in avoiding mistakes in application and interpretation. Finally, the book enables the reader to understand and conceptualize the overall flow of brain imaging data analysis, particularly for statisticians and data-scientists unfamiliar with this area. The state of the art method described in the book has a multivariate approach developed by the authors’ team. Since brain imaging data, generally, has a highly correlated and complex structure with large amounts of data, categorized into big data, the multivariate approach can be used as dimension reduction by following the application of statistical methods. The R package for most of the methods described is provided in the book. Understanding the background theory is helpful in implementing the software for original and creative applications and for an unbiased interpretation of the output. The book also explains new methods in a conceptual manner. These methodologies and packages are commonly applied in life science data analysis. Advanced methods to obtain novel insights are introduced, thereby encouraging the development of new methods and applications for research into medicine as a neuroscience.



The Statistical Analysis Of Functional Mri Data


The Statistical Analysis Of Functional Mri Data
DOWNLOAD

Author : Nicole Lazar
language : en
Publisher: Springer Science & Business Media
Release Date : 2008-06-10

The Statistical Analysis Of Functional Mri Data written by Nicole Lazar and has been published by Springer Science & Business Media this book supported file pdf, txt, epub, kindle and other format this book has been release on 2008-06-10 with Medical categories.


The study of brain function is one of the most fascinating pursuits of m- ern science. Functional neuroimaging is an important component of much of the current research in cognitive, clinical, and social psychology. The exci- ment of studying the brain is recognized in both the popular press and the scienti?c community. In the pages of mainstream publications, including The New York Times and Wired, readers can learn about cutting-edge research into topics such as understanding how customers react to products and - vertisements (“If your brain has a ‘buy button,’ what pushes it?”, The New York Times,October19,2004),howviewersrespondtocampaignads(“Using M. R. I. ’s to see politics on the brain,” The New York Times, April 20, 2004; “This is your brain on Hillary: Political neuroscience hits new low,” Wired, November 12,2007),howmen and womenreactto sexualstimulation (“Brain scans arouse researchers,”Wired, April 19, 2004), distinguishing lies from the truth (“Duped,” The New Yorker, July 2, 2007; “Woman convicted of child abuse hopes fMRI can prove her innocence,” Wired, November 5, 2007), and even what separates “cool” people from “nerds” (“If you secretly like Michael Bolton, we’ll know,” Wired, October 2004). Reports on pathologies such as autism, in which neuroimaging plays a large role, are also common (for - stance, a Time magazine cover story from May 6, 2002, entitled “Inside the world of autism”).



Multivariate Analysis Of Data In Sensory Science


Multivariate Analysis Of Data In Sensory Science
DOWNLOAD

Author : T. Naes
language : en
Publisher: Elsevier
Release Date : 1996-02-01

Multivariate Analysis Of Data In Sensory Science written by T. Naes and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1996-02-01 with Education categories.


The state-of-the-art of multivariate analysis in sensory science is described in this volume. Both methods for aggregated and individual sensory profiles are discussed. Processes and results are presented in such a way that they can be understood not only by statisticians but also by experienced sensory panel leaders and users of sensory analysis. The techniques presented are focused on examples and interpretation rather than on the technical aspects, with an emphasis on new and important methods which are possibly not so well known to scientists in the field. Important features of the book are discussions on the relationship among the methods with a strong accent on the connection between problems and methods. All procedures presented are described in relation to sensory data and not as completely general statistical techniques. Sensory scientists, applied statisticians, chemometricians, those working in consumer science, food scientists and agronomers will find this book of value.



Advanced And Multivariate Statistical Methods


Advanced And Multivariate Statistical Methods
DOWNLOAD

Author : Craig A. Mertler
language : en
Publisher: Taylor & Francis
Release Date : 2016-10-24

Advanced And Multivariate Statistical Methods written by Craig A. Mertler and has been published by Taylor & Francis this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-10-24 with Mathematics categories.


Ideal for non-math majors, Advanced and Multivariate Statistical Methods teaches students to interpret, present, and write up results for each statistical technique without overemphasizing advanced math. This highly applied approach covers the why, what, when and how of advanced and multivariate statistics in a way that is neither too technical nor too mathematical. Students also learn how to compute each technique using SPSS software. New to the Sixth Edition Instructor ancillaries are now available with the sixth edition. All SPSS directions and screenshots have been updated to Version 23 of the software. Student learning objectives have been added as a means for students to target their learning and for instructors to focus their instruction. Key words are reviewed and reinforced in the end of chapter material to ensure that students understand the vocabulary of advanced and multivariate statistics.



Multivariate Statistical Methods In Behavioral Research


Multivariate Statistical Methods In Behavioral Research
DOWNLOAD

Author : R. Darrell Bock
language : en
Publisher: Scientific Software International
Release Date : 1985

Multivariate Statistical Methods In Behavioral Research written by R. Darrell Bock and has been published by Scientific Software International this book supported file pdf, txt, epub, kindle and other format this book has been release on 1985 with Mathematics categories.




Making Sense Of Multivariate Data Analysis


Making Sense Of Multivariate Data Analysis
DOWNLOAD

Author : John Spicer
language : en
Publisher: SAGE
Release Date : 2005

Making Sense Of Multivariate Data Analysis written by John Spicer and has been published by SAGE this book supported file pdf, txt, epub, kindle and other format this book has been release on 2005 with Mathematics categories.


A short introduction to the subject, this text is aimed at students & practitioners in the behavioural & social sciences. It offers a conceptual overview of the foundations of MDA & of a range of specific techniques including multiple regression, logistic regression & log-linear analysis.



Analysis Of Neural Data


Analysis Of Neural Data
DOWNLOAD

Author : Robert E. Kass
language : en
Publisher: Springer
Release Date : 2014-07-08

Analysis Of Neural Data written by Robert E. Kass and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-07-08 with Medical categories.


Continual improvements in data collection and processing have had a huge impact on brain research, producing data sets that are often large and complicated. By emphasizing a few fundamental principles, and a handful of ubiquitous techniques, Analysis of Neural Data provides a unified treatment of analytical methods that have become essential for contemporary researchers. Throughout the book ideas are illustrated with more than 100 examples drawn from the literature, ranging from electrophysiology, to neuroimaging, to behavior. By demonstrating the commonality among various statistical approaches the authors provide the crucial tools for gaining knowledge from diverse types of data. Aimed at experimentalists with only high-school level mathematics, as well as computationally-oriented neuroscientists who have limited familiarity with statistics, Analysis of Neural Data serves as both a self-contained introduction and a reference work.



Multivariate Statistical Methods


Multivariate Statistical Methods
DOWNLOAD

Author : George A. Marcoulides
language : en
Publisher: Psychology Press
Release Date : 2014-01-14

Multivariate Statistical Methods written by George A. Marcoulides and has been published by Psychology Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2014-01-14 with Psychology categories.


Multivariate statistics refer to an assortment of statistical methods that have been developed to handle situations in which multiple variables or measures are involved. Any analysis of more than two variables or measures can loosely be considered a multivariate statistical analysis. An introductory text for students learning multivariate statistical methods for the first time, this book keeps mathematical details to a minimum while conveying the basic principles. One of the principal strategies used throughout the book--in addition to the presentation of actual data analyses--is pointing out the analogy between a common univariate statistical technique and the corresponding multivariate method. Many computer examples--drawing on SAS software --are used as demonstrations. Throughout the book, the computer is used as an adjunct to the presentation of a multivariate statistical method in an empirically oriented approach. Basically, the model adopted in this book is to first present the theory of a multivariate statistical method along with the basic mathematical computations necessary for the analysis of data. Subsequently, a real world problem is discussed and an example data set is provided for analysis. Throughout the presentation and discussion of a method, many references are made to the computer, output are explained, and exercises and examples with real data are included.



Multivariate Statistical Methods


Multivariate Statistical Methods
DOWNLOAD

Author : Jorge A. Navarro
language : en
Publisher: CRC Press
Release Date : 2016-11-03

Multivariate Statistical Methods written by Jorge A. Navarro and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2016-11-03 with Mathematics categories.


Multivariate Statistical Methods: A Primer provides an introductory overview of multivariate methods without getting too deep into the mathematical details. This fourth edition is a revised and updated version of this bestselling introductory textbook. It retains the clear and concise style of the previous editions of the book and focuses on examples from biological and environmental sciences. The major update with this edition is that R code has been included for each of the analyses described, although in practice any standard statistical package can be used. The original idea with this book still applies. This was to make it as short as possible and enable readers to begin using multivariate methods in an intelligent manner. With updated information on multivariate analyses, new references, and R code included, this book continues to provide a timely introduction to useful tools for multivariate statistical analysis.