Essentials Of Multivariate Data Analysis
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Essentials Of Multivariate Data Analysis
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Author : Neil H. Spencer
language : en
Publisher: CRC Press
Release Date : 2013-12-17
Essentials Of Multivariate Data Analysis written by Neil H. Spencer and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2013-12-17 with Mathematics categories.
Since most datasets contain a number of variables, multivariate methods are helpful in answering a variety of research questions. Accessible to students and researchers without a substantial background in statistics or mathematics, Essentials of Multivariate Data Analysis explains the usefulness of multivariate methods in applied research. Unlike m
Applied Statistics And Multivariate Data Analysis For Business And Economics
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Author : Thomas Cleff
language : en
Publisher: Springer
Release Date : 2019-07-10
Applied Statistics And Multivariate Data Analysis For Business And Economics written by Thomas Cleff and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-10 with Business & Economics categories.
This textbook will familiarize students in economics and business, as well as practitioners, with the basic principles, techniques, and applications of applied statistics, statistical testing, and multivariate data analysis. Drawing on practical examples from the business world, it demonstrates the methods of univariate, bivariate, and multivariate statistical analysis. The textbook covers a range of topics, from data collection and scaling to the presentation and simple univariate analysis of quantitative data, while also providing advanced analytical procedures for assessing multivariate relationships. Accordingly, it addresses all topics typically covered in university courses on statistics and advanced applied data analysis. In addition, it does not limit itself to presenting applied methods, but also discusses the related use of Excel, SPSS, and Stata.
Matrix Based Introduction To Multivariate Data Analysis
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Author : Kohei Adachi
language : en
Publisher: Springer Nature
Release Date : 2020-05-20
Matrix Based Introduction To Multivariate Data Analysis written by Kohei Adachi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-05-20 with Mathematics categories.
This is the first textbook that allows readers who may be unfamiliar with matrices to understand a variety of multivariate analysis procedures in matrix forms. By explaining which models underlie particular procedures and what objective function is optimized to fit the model to the data, it enables readers to rapidly comprehend multivariate data analysis. Arranged so that readers can intuitively grasp the purposes for which multivariate analysis procedures are used, the book also offers clear explanations of those purposes, with numerical examples preceding the mathematical descriptions. Supporting the modern matrix formulations by highlighting singular value decomposition among theorems in matrix algebra, this book is useful for undergraduate students who have already learned introductory statistics, as well as for graduate students and researchers who are not familiar with matrix-intensive formulations of multivariate data analysis. The book begins by explaining fundamental matrix operations and the matrix expressions of elementary statistics. Then, it offers an introduction to popular multivariate procedures, with each chapter featuring increasing advanced levels of matrix algebra. Further the book includes in six chapters on advanced procedures, covering advanced matrix operations and recently proposed multivariate procedures, such as sparse estimation, together with a clear explication of the differences between principal components and factor analyses solutions. In a nutshell, this book allows readers to gain an understanding of the latest developments in multivariate data science.
Multivariate Analysis
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Author : Klaus Backhaus
language : en
Publisher: Springer Nature
Release Date : 2023-06-28
Multivariate Analysis written by Klaus Backhaus and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-06-28 with Business & Economics categories.
Data can be extremely valuable if we are able to extract information from them. This is why multivariate data analysis is essential for business and science. This book offers an easy-to-understand introduction to the most relevant methods of multivariate data analysis. It is strictly application-oriented, requires little knowledge of mathematics and statistics, demonstrates the procedures with numerical examples and illustrates each method via a case study solved with IBM’s statistical software package SPSS. Extensions of the methods and links to other procedures are discussed and recommendations for application are given. An introductory chapter presents the basic ideas of the multivariate methods covered in the book and refreshes statistical basics which are relevant to all methods. For the 2nd edition, all chapters were checked and calculated using the current version of IBM SPSS. Contents Introduction to empirical data analysis Regression analysis Analysis of variance Discriminant analysis Logistic regression Contingency analysis Factor analysis Cluster analysis Conjoint analysis The original German version is now available in its 17th edition. In 2015, this book was honored by the Federal Association of German Market and Social Researchers as “the textbook that has shaped market research and practice in German-speaking countries”. A Chinese version is available in its 3rd edition. On the website www.multivariate-methods.info, the authors further analyze the data with Excel and R and provide additional material to facilitate the understanding of the different multivariate methods. In addition, interactive flashcards are available to the reader for reviewing selected focal points. Download the Springer Nature Flashcards App and use exclusive content to test your knowledge.
Modern Statistical Methods For Spatial And Multivariate Data
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Author : Norou Diawara
language : en
Publisher: Springer
Release Date : 2019-07-11
Modern Statistical Methods For Spatial And Multivariate Data written by Norou Diawara and has been published by Springer this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-07-11 with Mathematics categories.
This contributed volume features invited papers on current models and statistical methods for spatial and multivariate data. With a focus on recent advances in statistics, topics include spatio-temporal aspects, classification techniques, the multivariate outcomes with zero and doubly-inflated data, discrete choice modelling, copula distributions, and feasible algorithmic solutions. Special emphasis is placed on applications such as the use of spatial and spatio-temporal models for rainfall in South Carolina and the multivariate sparse areal mixed model for the Census dataset for the state of Iowa. Articles use simulated and aggregated data examples to show the flexibility and wide applications of proposed techniques. Carefully peer-reviewed and pedagogically presented for a broad readership, this volume is suitable for graduate and postdoctoral students interested in interdisciplinary research. Researchers in applied statistics and sciences will find this book an important resource on the latest developments in the field. In keeping with the STEAM-H series, the editors hope to inspire interdisciplinary understanding and collaboration.
Applied Multivariate Analysis
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Author : Neil H. Timm
language : en
Publisher: Springer Science & Business Media
Release Date : 2007-06-21
Applied Multivariate Analysis written by Neil H. Timm 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 2007-06-21 with Mathematics categories.
Univariate statistical analysis is concerned with techniques for the analysis of a single random variable. This book is about applied multivariate analysis. It was written to p- vide students and researchers with an introduction to statistical techniques for the ana- sis of continuous quantitative measurements on several random variables simultaneously. While quantitative measurements may be obtained from any population, the material in this text is primarily concerned with techniques useful for the analysis of continuous obser- tions from multivariate normal populations with linear structure. While several multivariate methods are extensions of univariate procedures, a unique feature of multivariate data an- ysis techniques is their ability to control experimental error at an exact nominal level and to provide information on the covariance structure of the data. These features tend to enhance statistical inference, making multivariate data analysis superior to univariate analysis. While in a previous edition of my textbook on multivariate analysis, I tried to precede a multivariate method with a corresponding univariate procedure when applicable, I have not taken this approach here. Instead, it is assumed that the reader has taken basic courses in multiple linear regression, analysis of variance, and experimental design. While students may be familiar with vector spaces and matrices, important results essential to multivariate analysis are reviewed in Chapter 2. I have avoided the use of calculus in this text.
Making Sense Of Multivariate Data Analysis
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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.
Essentials Of Data Analysis
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Author : Agasti Khatri
language : en
Publisher: Educohack Press
Release Date : 2025-02-20
Essentials Of Data Analysis written by Agasti Khatri and has been published by Educohack Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-02-20 with Computers categories.
"Essentials of Data Analysis" is an indispensable guide that navigates readers through the world of data-driven decision-making. This book presents essential concepts, techniques, and tools in an accessible and user-friendly manner. It serves as a trusted companion for both beginners and professionals in their data analysis journey. We start by laying a solid foundation in data analysis principles, providing a comprehensive understanding of key concepts and methodologies. The book delves into practical techniques for data manipulation, visualization, and exploration, equipping readers with the skills to extract actionable insights from raw data. Real-world examples, case studies, and hands-on exercises bring abstract concepts to life. We emphasize the ethical and responsible use of data, guiding readers through ethical considerations, privacy concerns, and regulatory requirements. This fosters a culture of ethical awareness and accountability. Additionally, we explore emerging trends and technologies shaping the future of data analysis, such as artificial intelligence, machine learning, augmented analytics, and edge computing. By adopting innovative techniques, readers can drive meaningful change within their organizations. "Essentials of Data Analysis" is a valuable resource for enhancing analytical skills, advancing careers, and understanding the role of data in decision-making.
Introduction To Multivariate Analysis
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Author : Chris Chatfield
language : en
Publisher: CRC Press
Release Date : 1981-05-15
Introduction To Multivariate Analysis written by Chris Chatfield and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 1981-05-15 with Mathematics categories.
This book provides an introduction to the analysis of multivariate data.It describes multivariate probability distributions, the preliminary analysisof a large -scale set of data, princ iple component and factor analysis, traditional normal theory material, as well as multidimensional scaling andcluster analysis.Introduction to Multivariate Analysis provides a reasonable blend oftheory and practice. Enough theory is given to introduce the concepts andto make the topics mathematically interesting. In addition the authors discussthe use (and misuse) of the techniques in pra ctice and present appropriatereal-life examples from a variety of areas includ ing agricultural research, soc iology and crim inology. The book should be suitable both for researchworkers and as a text for students taking a course on multivariate analysis.
Multivariate Statistical Methods
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Author : Bryan F. J. Manly
language : en
Publisher: Chapman & Hall/CRC
Release Date : 2017-09-30
Multivariate Statistical Methods written by Bryan F. J. Manly and has been published by Chapman & Hall/CRC this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-09-30 with 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.