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Author: Brian Everitt Publisher: Springer Science & Business Media ISBN: 1441996508 Category : Mathematics Languages : en Pages : 284
Book Description
The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.
Author: Farit Mochamad Afendi Publisher: European Alliance for Innovation ISBN: 1631902202 Category : Education Languages : en Pages : 610
Book Description
This conference serves as a means of presenting and discussing various research results among academics, researchers, and practitioners in the fields of statistics, analytics, computing, data science, and its application. Based on 110 papers that have been presented there are three main topics as the focus of the discussion, namely Statistical Modeling, Predictive Analytics, and Pattern Learning. The approach is in the form of a study to obtain a valid methodology for extracting, collecting, storing, analyzing, and visualizing data including those derived from big data. The application studies cover various fields such as agriculture, climate, energy, industry, business, social, and so on. The conference is expected to be able to provide solutions to various problems in various fields through statistical and analytical approaches.
Author: Brian Everitt Publisher: Springer Science & Business Media ISBN: 1441996508 Category : Mathematics Languages : en Pages : 284
Book Description
The majority of data sets collected by researchers in all disciplines are multivariate, meaning that several measurements, observations, or recordings are taken on each of the units in the data set. These units might be human subjects, archaeological artifacts, countries, or a vast variety of other things. In a few cases, it may be sensible to isolate each variable and study it separately, but in most instances all the variables need to be examined simultaneously in order to fully grasp the structure and key features of the data. For this purpose, one or another method of multivariate analysis might be helpful, and it is with such methods that this book is largely concerned. Multivariate analysis includes methods both for describing and exploring such data and for making formal inferences about them. The aim of all the techniques is, in general sense, to display or extract the signal in the data in the presence of noise and to find out what the data show us in the midst of their apparent chaos. An Introduction to Applied Multivariate Analysis with R explores the correct application of these methods so as to extract as much information as possible from the data at hand, particularly as some type of graphical representation, via the R software. Throughout the book, the authors give many examples of R code used to apply the multivariate techniques to multivariate data.
Author: Mahya Hemmati Publisher: CRC Press ISBN: 1000406962 Category : Business & Economics Languages : en Pages : 298
Book Description
In today’s competitive markets, considering the demand and the supply chain sides is crucial to keeping revenue and customer satisfaction maximized. Managing and planning demand play a vital role in the sustainability of a company. This is the first book to the discuss managerial, mathematical, and conceptual framework of influencing factors on demand along with accurate mathematical analyses to evaluate and raise revenue. The book provides an understanding of the key elements that impact buyer demand. It presents the mathematical relationship between the influencing factors and the demand functions. It discusses the methods used for inspiring demand, how to measure demand dependency on components such as price, quality, and inventory, and it helps management improve alignment between supply and demand by affecting the level and understanding of the role within supply chain management (SCM). This book is applicable for the professional as well as for academia. It can help those working in SCM, project management, production, inventory control, scheduling, engineering management, retail management, and operations management.
Author: Joseph Hair Publisher: Pearson Higher Ed ISBN: 0133792684 Category : Business & Economics Languages : en Pages : 816
Book Description
This is the eBook of the printed book and may not include any media, website access codes, or print supplements that may come packaged with the bound book. For graduate and upper-level undergraduate marketing research courses. For over 30 years, Multivariate Data Analysis has provided readers with the information they need to understand and apply multivariate data analysis. Hair et. al provides an applications-oriented introduction to multivariate analysis for the non-statistician. By reducing heavy statistical research into fundamental concepts, the text explains to readers how to understand and make use of the results of specific statistical techniques. In this Seventh Edition, the organization of the chapters has been greatly simplified. New chapters have been added on structural equations modeling, and all sections have been updated to reflect advances in technology, capability, and mathematical techniques.
Author: Richard J. Harris Publisher: Psychology Press ISBN: 1135555435 Category : Psychology Languages : en Pages : 632
Book Description
Drawing upon more than 30 years of experience in working with statistics, Dr. Richard J. Harris has updated A Primer of Multivariate Statistics to provide a model of balance between how-to and why. This classic text covers multivariate techniques with a taste of latent variable approaches. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis. This edition retains its conversational writing style while focusing on classical techniques. The book gives the reader a feel for why one should consider diving into more detailed treatments of computer-modeling and latent-variable techniques, such as non-recursive path analysis, confirmatory factor analysis, and hierarchical linear modeling. Throughout the book there is a focus on the importance of describing and testing one's interpretations of the emergent variables that are produced by multivariate analysis.
Author: Robert L. Mason Publisher: SIAM ISBN: 0898714966 Category : Technology & Engineering Languages : en Pages : 271
Book Description
Detailed coverage of the practical aspects of multivariate statistical process control (MVSPC) based on the application of Hotelling's T2 statistic. MVSPC is the application of multivariate statistical techniques to improve the quality and productivity of an industrial process. Provides valuable insight into the T2 statistic.
Author: Ajay Sohoni Publisher: John Wiley & Sons ISBN: 1119803241 Category : Business & Economics Languages : en Pages : 291
Book Description
Discover how to move forward with your own company’s digital transformation with this accessible new resource from a global leader in his field In The Digital Frontier, experienced executive and distinguished author Ajay Sohoni delivers a relatable and readable reference for corporate executives who need the knowledge and confidence to build lasting digital change within their enterprise. From marketing to commercial, supply chain, and finance, the book offers actionable insights in an accessible format, full of anecdotes, humor, and case examples. You’ll learn which areas to focus on and which not to worry about as you craft your own custom transformation journey. In the book, you’ll also find: A demystification of the startup world for executives and an explanation of why unicorns exist (and so often ultimately fail) A detailed description of the digital transformation gripping companies across a variety of industries in functional areas including advertising, engagement, commerce, product development, manufacturing, and corporate functions A simplified 4-stage framework for companies to start from scratch and build valuable use cases Perfect for executives in consumer-facing companies, corporate managers and leaders, business unit heads and management teams, The Digital Frontier is also an indispensable guide for digital non-natives trying to make sense of, and keep up with, the rapidly changing world around them.
Author: Abdelmonem Afifi Publisher: CRC Press ISBN: 1351788906 Category : Mathematics Languages : en Pages : 534
Book Description
This is the sixth edition of a popular textbook on multivariate analysis. Well-regarded for its practical and accessible approach, with excellent examples and good guidance on computing, the book is particularly popular for teaching outside statistics, i.e. in epidemiology, social science, business, etc. The sixth edition has been updated with a new chapter on data visualization, a distinction made between exploratory and confirmatory analyses and a new section on generalized estimating equations and many new updates throughout. This new edition will enable the book to continue as one of the leading textbooks in the area, particularly for non-statisticians. Key Features: Provides a comprehensive, practical and accessible introduction to multivariate analysis. Keeps mathematical details to a minimum, so particularly geared toward a non-statistical audience. Includes lots of detailed worked examples, guidance on computing, and exercises. Updated with a new chapter on data visualization.
Author: Brian Everitt
Author: Farit Mochamad Afendi
Author: Brian Everitt
Author: Mahya Hemmati
Author: Joseph Hair
Author: Richard J. Harris
Author: Wolfgang Karl Härdle
Author: Robert L. Mason
Author: Kamhon Kan
Author: Ajay Sohoni
Author: Abdelmonem Afifi