Multivariate Exploratory Data Analysis
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Exploratory Multivariate Analysis By Example Using R
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Author : Francois Husson
language : en
Publisher: CRC Press
Release Date : 2010-11-15
Exploratory Multivariate Analysis By Example Using R written by Francois Husson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2010-11-15 with Mathematics categories.
Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and hierarchical cluster analysis. The authors take a geometric point of view that provides a unified vision for exploring multivariate data tables. Within this framework, they present the principles, indicators, and ways of representing and visualizing objects that are common to the exploratory methods. The authors show how to use categorical variables in a PCA context in which variables are quantitative, how to handle more than two categorical variables in a CA context in which there are originally two variables, and how to add quantitative variables in an MCA context in which variables are categorical. They also illustrate the methods and the ways they can be exploited using examples from various fields. Throughout the text, each result correlates with an R command accessible in the FactoMineR package developed by the authors. All of the data sets and code are available at http://factominer.free.fr/book By using the theory, examples, and software presented in this book, readers will be fully equipped to tackle real-life multivariate data.
Multivariate Exploratory Data Analysis
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Author : Allen Yates
language : en
Publisher:
Release Date : 1987
Multivariate Exploratory Data Analysis written by Allen Yates and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 1987 with Mathematics categories.
Exploratory Data Analysis With Matlab
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Author : Wendy L. Martinez
language : en
Publisher: CRC Press
Release Date : 2004-11-29
Exploratory Data Analysis With Matlab written by Wendy L. Martinez and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2004-11-29 with Business & Economics categories.
Exploratory data analysis (EDA) was conceived at a time when computers were not widely used, and thus computational ability was rather limited. As computational sophistication has increased, EDA has become an even more powerful process for visualizing and summarizing data before making model assumptions to generate hypotheses, encompassing larger and more complex data sets. There are many resources for those interested in the theory of EDA, but this is the first book to use MATLAB to illustrate the computational aspects of this discipline. Exploratory Data Analysis with MATLAB presents the methods of EDA from a computational perspective. The authors extensively use MATLAB code and algorithm descriptions to provide state-of-the-art techniques for finding patterns and structure in data. Addressing theory, they also incorporate many annotated references to direct readers to the more theoretical aspects of the methods. The book presents an approach using the basic functions from MATLAB and the MATLAB Statistics Toolbox, in order to be more accessible and enduring. It also contains pseudo-code to enable users of other software packages to implement the algorithms. This text places the tools needed to implement EDA theory at the fingertips of researchers, applied mathematicians, computer scientists, engineers, and statisticians by using a practical/computational approach.
Exploratory And Multivariate Data Analysis
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Author : Michel Jambu
language : en
Publisher: Elsevier
Release Date : 1991-09-09
Exploratory And Multivariate Data Analysis written by Michel Jambu and has been published by Elsevier this book supported file pdf, txt, epub, kindle and other format this book has been release on 1991-09-09 with Mathematics categories.
With a useful index of notations at the beginning, this book explains and illustrates the theory and application of data analysis methods from univariate to multidimensional and how to learn and use them efficiently. This book is well illustrated and is a useful and well-documented review of the most important data analysis techniques. - Describes, in detail, exploratory data analysis techniques from the univariate to the multivariate ones - Features a complete description of correspondence analysis and factor analysis techniques as multidimensional statistical data analysis techniques, illustrated with concrete and understandable examples - Includes a modern and up-to-date description of clustering algorithms with many properties which gives a new role of clustering in data analysis techniques
Exploratory Multivariate Analysis By Example Using R
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Author : Francois Husson
language : en
Publisher: CRC Press
Release Date : 2020-09-30
Exploratory Multivariate Analysis By Example Using R written by Francois Husson and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2020-09-30 with categories.
Full of real-world case studies and practical advice, Exploratory Multivariate Analysis by Example Using R, Second Edition focuses on four fundamental methods of multivariate exploratory data analysis that are most suitable for applications. It covers principal component analysis (PCA) when variables are quantitative, correspondence analysis (CA) and multiple correspondence analysis (MCA) when variables are categorical, and hierarchical cluster analysis. The authors take a geometric point of view that provides a unified vision for exploring multivariate data tables. Within this framework, they present the principles, indicators, and ways of representing and visualising objects that are common to the exploratory methods. The authors show how to use categorical variables in a PCA context in which variables are quantitative, how to handle more than two categorical variables in a CA context in which there are originally two variables, and how to add quantitative variables in an MCA context in which variables are categorical. They also illustrate the methods using examples from various fields, with related R code accessible in the FactoMineR package developed by the authors.
Data Visualization And Storytelling With Tableau
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Author : Mamta Mittal
language : en
Publisher: CRC Press
Release Date : 2024-06-28
Data Visualization And Storytelling With Tableau written by Mamta Mittal and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-06-28 with Computers categories.
Tableau, one of the most widely used visualization tools, helps in illustrating the ideas of data visualization and storytelling. Through Tableau’s Data Visualization and Storytelling feature, aspiring data scientists and analysts can develop their visual analytics skills and use them in both academic and business contexts. Data Visualization and Storytelling with Tableau enables budding data analysts and data scientists to develop and sharpen their skills in the field of visual analytics and apply them in business scenarios as well as in academic context. This book approaches the Data Visualization workflow from a practical point of view, emphasizing the steps involved and the outcomes attained. A major focus of this book is the application and deployment of real-time case studies. Later chapters in this book provide comprehensive coverage for advanced topics such as data storytelling, data insights, color selection in graphs, publishing in tableau public, and misleading visualizations. Thus, this book emphasizes the need to visually examine and evaluate data through stories and interactive dashboards that are made up of appropriate graphs and charts. The case studies covered in this book are a natural extension of the visualization topics that are covered in each chapter. The intention is to empower readers to generate various dashboards, stories, graphs, charts, and maps to visualize and analyze data and support decision-making in business. Advanced charts that are pertinent to project management operations are also thoroughly explored, including comparison charts, distribution charts, composition charts, and maps. All these concepts will lay a solid foundation for data visualization applications in the minds of readers. This book is meant for data analysts, computer scientists/engineers, and industry professionals who are interested in creating different types of visualization graphs for a given data problem and drawing interesting insights from the plotted trends in order to make better business decisions in the future. Features: Introduces the world of Business Intelligence to readers through visualizations in Tableau. Discusses the need and relevance of each business graph with the help of a corresponding real-time case study. Explores the art of picking a suitable graph with an appropriate color scheme for a given scenario. Establishes the process of gaining relevant insights from the analysis of visualizations created. Provides guidance in creating innovative dashboards and driving the readers through the process of innovative storytelling with data in Tableau. Implements the concept of Exploratory Data Analysis (EDA) in Tableau.
Exploratory Analysis Of Multivariate Image Data
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Author : Axel Saalbach
language : en
Publisher:
Release Date : 2006
Exploratory Analysis Of Multivariate Image Data written by Axel Saalbach and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2006 with categories.
Applied Data Mining
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Author : Paolo Giudici
language : en
Publisher: John Wiley & Sons
Release Date : 2005-09-27
Applied Data Mining written by Paolo Giudici 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 2005-09-27 with Computers categories.
Data mining can be defined as the process of selection, explorationand modelling of large databases, in order to discover models andpatterns. The increasing availability of data in the currentinformation society has led to the need for valid tools for itsmodelling and analysis. Data mining and applied statistical methodsare the appropriate tools to extract such knowledge from data.Applications occur in many different fields, including statistics,computer science, machine learning, economics, marketing andfinance. This book is the first to describe applied data mining methodsin a consistent statistical framework, and then show how they canbe applied in practice. All the methods described are eithercomputational, or of a statistical modelling nature. Complexprobabilistic models and mathematical tools are not used, so thebook is accessible to a wide audience of students and industryprofessionals. The second half of the book consists of nine casestudies, taken from the author's own work in industry, thatdemonstrate how the methods described can be applied to realproblems. Provides a solid introduction to applied data mining methods ina consistent statistical framework Includes coverage of classical, multivariate and Bayesianstatistical methodology Includes many recent developments such as web mining,sequential Bayesian analysis and memory based reasoning Each statistical method described is illustrated with real lifeapplications Features a number of detailed case studies based on appliedprojects within industry Incorporates discussion on software used in data mining, withparticular emphasis on SAS Supported by a website featuring data sets, software andadditional material Includes an extensive bibliography and pointers to furtherreading within the text Author has many years experience teaching introductory andmultivariate statistics and data mining, and working on appliedprojects within industry A valuable resource for advanced undergraduate and graduatestudents of applied statistics, data mining, computer science andeconomics, as well as for professionals working in industry onprojects involving large volumes of data - such as in marketing orfinancial risk management.
Data Science For Business And Decision Making
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Author : Luiz Paulo Favero
language : en
Publisher: Academic Press
Release Date : 2019-04-11
Data Science For Business And Decision Making written by Luiz Paulo Favero and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2019-04-11 with Business & Economics categories.
Data Science for Business and Decision Making covers both statistics and operations research while most competing textbooks focus on one or the other. As a result, the book more clearly defines the principles of business analytics for those who want to apply quantitative methods in their work. Its emphasis reflects the importance of regression, optimization and simulation for practitioners of business analytics. Each chapter uses a didactic format that is followed by exercises and answers. Freely-accessible datasets enable students and professionals to work with Excel, Stata Statistical Software®, and IBM SPSS Statistics Software®. - Combines statistics and operations research modeling to teach the principles of business analytics - Written for students who want to apply statistics, optimization and multivariate modeling to gain competitive advantages in business - Shows how powerful software packages, such as SPSS and Stata, can create graphical and numerical outputs
Data Analysis And Graphics Using R
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Author : John Maindonald
language : en
Publisher: Cambridge University Press
Release Date : 2003-08-04
Data Analysis And Graphics Using R written by John 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 2003-08-04 with Computers categories.
Modern statistical software systems provide sophisticated tools for researchers who need to manipulate and display their data. Using such systems requires training both in the software itself and in the statistical methods that it relies on. Concentrating on the freely available R system, this book demonstrates recently implemented approaches and methods in statistical analysis. The authors introduce elementary concepts in statistics through examples of real-world data analysis drawn from the authors' experience, both as teachers and as consultants. R code and data sets for all examples are available on the Internet. This emphasis on practical methodology combined with a tutorial approach makes the book accessible to anyone with a knowledge of undergraduate statistics, whether an upper-graduate student, a researcher, or a practising scientist or statistician. The methods demonstrated are suitable for use in a wide variety of disciplines, from social sciences to medicine, engineering and science.